Publications by authors named "Omer T Inan"

124 Publications

Machine learning to extract muscle fascicle length changes from dynamic ultrasound images in real-time.

PLoS One 2021 26;16(5):e0246611. Epub 2021 May 26.

School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.

Background And Objective: Dynamic muscle fascicle length measurements through B-mode ultrasound have become popular for the non-invasive physiological insights they provide regarding musculoskeletal structure-function. However, current practices typically require time consuming post-processing to track muscle length changes from B-mode images. A real-time measurement tool would not only save processing time but would also help pave the way toward closed-loop applications based on feedback signals driven by in vivo muscle length change patterns. In this paper, we benchmark an approach that combines traditional machine learning (ML) models with B-mode ultrasound recordings to obtain muscle fascicle length changes in real-time. To gauge the utility of this framework for 'in-the-loop' applications, we evaluate accuracy of the extracted muscle length change signals against time-series' derived from a standard, post-hoc automated tracking algorithm.

Methods: We collected B-mode ultrasound data from the soleus muscle of six participants performing five defined ankle motion tasks: (a) seated, constrained ankle plantarflexion, (b) seated, free ankle dorsi/plantarflexion, (c) weight-bearing, calf raises (d) walking, and then a (e) mix. We trained machine learning (ML) models by pairing muscle fascicle lengths obtained from standardized automated tracking software (UltraTrack) with the respective B-mode ultrasound image input to the tracker, frame-by-frame. Then we conducted hyperparameter optimizations for five different ML models using a grid search to find the best performing parameters for a combination of high correlation and low RMSE between ML and UltraTrack processed muscle fascicle length trajectories. Finally, using the global best model/hyperparameter settings, we comprehensively evaluated training-testing outcomes within subject (i.e., train and test on same subject), cross subject (i.e., train on one subject, test on another) and within/direct cross task (i.e., train and test on same subject, but different task).

Results: Support vector machine (SVM) was the best performing model with an average r = 0.70 ±0.34 and average RMSE = 2.86 ±2.55 mm across all direct training conditions and average r = 0.65 ±0.35 and average RMSE = 3.28 ±2.64 mm when optimized for all cross-participant conditions. Comparisons between ML vs. UltraTrack (i.e., ground truth) tracked muscle fascicle length versus time data indicated that ML tracked images reliably capture the salient qualitative features in ground truth length change data, even when correlation values are on the lower end. Furthermore, in the direct training, calf raises condition, which is most comparable to previous studies validating automated tracking performance during isolated contractions on a dynamometer, our ML approach yielded 0.90 average correlation, in line with other accepted tracking methods in the field.

Conclusions: By combining B-mode ultrasound and classical ML models, we demonstrate it is possible to achieve real-time tracking of human soleus muscle fascicles across a number of functionally relevant contractile conditions. This novel sensing modality paves the way for muscle physiology in-the-loop applications that could be used to modify gait via biofeedback or unlock novel wearable device control techniques that could enable restored or augmented locomotion performance.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0246611PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8153491PMC
May 2021

An Interpretable Experimental Data Augmentation Method to Improve Knee Health Classification Using Joint Acoustic Emissions.

Ann Biomed Eng 2021 May 13. Epub 2021 May 13.

School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.

The characteristics of joint acoustic emissions (JAEs) measured from the knee have been shown to contain information regarding underlying joint health. Researchers have developed methods to process JAE measurements and combined them with machine learning algorithms for knee injury diagnosis. While these methods are based on JAEs measured in controlled settings, we anticipate that JAE measurements could enable accessible and affordable diagnosis of acute knee injuries also in field-deployable settings. However, in such settings, the noise and interference would be greater than in sterile, laboratory environments, which could decrease the performance of existing knee health classification methods using JAEs. To address the need for an objective noise and interference detection method for JAE measurements as a step towards field-deployable settings, we propose a novel experimental data augmentation method to locate and then, remove the corrupted parts of JAEs measured in clinical settings. In the clinic, we recruited 30 participants, and collected data from both knees, totaling 60 knees (36 healthy and 24 injured knees) to be used subsequently for knee health classification. We also recruited 10 healthy participants to collect artifact and joint sounds (JS) click templates, which are audible, short duration and high amplitude JAEs from the knee. Spectral and temporal features were extracted, and clinical data was augmented in five-dimensional subspace by fusing the existing clinical dataset into experimentally collected templates. Then knee scores were calculated by training and testing a linear soft classifier utilizing leave-one-subject-out cross-validation (LOSO-CV). The area under the curve (AUC) was 0.76 for baseline performance without any window removal with a logistic regression classifier (sensitivity = 0.75, specificity = 0.78). We obtained an AUC of 0.86 with the proposed algorithm (sensitivity = 0.80, specificity = 0.89), and on average, 95% of all clinical data was used to achieve this performance. The proposed algorithm improved knee health classification performance by the added information through identification and collection of common artifact sources in JAE measurements. This method when combined with wearable systems could provide clinically relevant supplementary information for both underserved populations and individuals requiring point-of-injury diagnosis in field-deployable settings.
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http://dx.doi.org/10.1007/s10439-021-02788-xDOI Listing
May 2021

Use of Ballistocardiography to Monitor Cardiovascular Hemodynamics in Preeclampsia.

Womens Health Rep (New Rochelle) 2021 20;2(1):97-105. Epub 2021 Apr 20.

Division of Cardiology, Department of Internal Medicine, University of California San Francisco, San Francisco, California, USA.

Pregnancy requires a complex physiological adaptation of the maternal cardiovascular system, which is disrupted in women with pregnancies complicated by preeclampsia, putting them at higher risk of future cardiovascular events. The measurement of body movements in response to cardiac ejection ballistocardiogram (BCG) can be used to assess cardiovascular hemodynamics noninvasively in women with preeclampsia. Using a previously validated, modified weighing scale for assessment of cardiovascular hemodynamics through measurement of BCG and electrocardiogram (ECG) signals, we collected serial measurements throughout pregnancy and postpartum and analyzed data in 30 women with preeclampsia and 23 normotensive controls. Using BCG and ECG signals, we extracted measures of cardiac output, J-wave amplitude × heart rate (J-amp × HR). Mixed-effect models with repeated measures were used to compare J-amp × HRs between groups at different time points in pregnancy and postpartum. In normotensive controls, the J-amp × HR was significantly lower early postpartum (E-PP) compared with the second trimester (T2;  = 0.016) and third trimester (T3;  = 0.001). Women with preeclampsia had a significantly lower J-amp × HR compared with normotensive controls during the first trimester (T1;  = 0.026). In the preeclampsia group, there was a trend toward an increase in J-amp × HR from T1 to T2 and then a drop in J-amp × HR at T3 and further drop at E-PP. We observe cardiac hemodynamic changes consistent with those reported using well-validated tools. In pregnancies complicated by preeclampsia, the maximal force of contraction is lower, suggesting lower cardiac output and a trend in hemodynamics consistent with the hyperdynamic disease model of preeclampsia.
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http://dx.doi.org/10.1089/whr.2020.0127DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080913PMC
April 2021

Inertial Measurements for Tongue Motion Tracking Based on Magnetic Localization with Orientation Compensation.

IEEE Sens J 2021 Mar 22;21(6):7964-7971. Epub 2020 Dec 22.

School of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA.

Permanent magnet localization (PML) is designed for applications requiring non-line-of-sight motion tracking with millimetric accuracy. Current PML-based tongue tracking is not only impractical for daily use due to many sensors being placed around the mouth, but also requires a large training set of tracer motion. Our method was designed to overcome these shortcomings by generating a local magnetic field and removing the need for the localization to be trained with tracer rotations. An inertial measurement unit (IMU) is used as a tracer that moves in a local magnetic field generated by a magnet strip. The magnetic strength can be optimized to enable the strip to be placed further away from the tracer, thus hidden from view. The tracer is small (6×6×0.8 mm) to reduce hindrance to natural tongue movements, and the strip is designed to be worn as a neckband. The IMU's magnetometer measures the local magnetic field which is compensated for the tracer's orientation by using the IMU's accelerometer and gyroscope. The orientation-compensated magnetic measurements are then fed into a localization algorithm that estimates the tracer's 3D position. The objective of this study is to evaluate the tracking accuracy of our method. In a 8×8×5 cm volume, positional errors of 1.6 mm (median) and 2.4 mm (third quartile, Q3) were achieved on a tracer being rotated ±50° along both pitch and roll. These results indicate this technology is promising for tongue tracking applications.
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http://dx.doi.org/10.1109/jsen.2020.3046469DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7978385PMC
March 2021

Vibration Stimulation as a Non-Invasive Approach to Monitor the Severity of Meniscus Tears.

IEEE Trans Neural Syst Rehabil Eng 2021 2;29:350-359. Epub 2021 Mar 2.

Musculoskeletal disorders and injuries are one of the most prevalent medical conditions across age groups. Due to a high load-bearing function, the knee is particularly susceptible to injuries such as meniscus tears. Imaging techniques are commonly used to assess meniscus injuries, though this approach suffers from limitations including high cost, need for skilled personnel, and confinement to laboratory or clinical settings. Vibration-based structural monitoring methods in the form of acoustic emission analysis and vibration stimulation have the potential to address the limits associated with current diagnostic technologies. In this study, an active vibration measurement technique is employed to investigate the presence and severity of meniscus tear in cadaver limbs. In a highly controlled ex vivo experimental design, a series of cadaver knees (n =6) were evaluated under an external vibration, and the frequency response of the joint was analyzed to differentiate the intact and affected samples. Four stages of knee integrity were considered: baseline, sham surgery, meniscus tear, and meniscectomy. Analyzing the frequency response of injured legs showed significant changes compared to the baseline and sham stages at selected frequency bandwidths. Furthermore, a qualitative analytical model of the knee was developed based on the Euler-Bernoulli beam theory representing the meniscus tear as a change in the local stiffness of the system. Similar trends in frequency response modulation were observed in the experimental results and analytical model. These findings serve as a foundation for further development of wearable devices for detection and grading of meniscus tear and for improving our understanding of the physiological effects of injuries on the vibration characteristics of the knee. Such systems can also aid in quantifying rehabilitation progress following reconstructive surgery and / or during physical therapy.
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http://dx.doi.org/10.1109/TNSRE.2021.3050439DOI Listing
March 2021

Detection of Meniscal Tear Effects on Tibial Vibration Using Passive Knee Sound Measurements.

IEEE Trans Biomed Eng 2021 Jul 17;68(7):2241-2250. Epub 2021 Jun 17.

Objective: To evaluate whether non-invasive knee sound measurements can provide information related to the underlying structural changes in the knee following meniscal tear. These changes are explained using an equivalent vibrational model of the knee-tibia structure.

Methods: First, we formed an analytical model by modeling the tibia as a cantilever beam with the fixed end being the knee. The knee end was supported by three lumped components with features corresponding with tibial stiffnesses, and meniscal damping effect. Second, we recorded knee sounds from 46 healthy legs and 9 legs with acute meniscal tears (n = 34 subjects). We developed an acoustic event ("click") detection algorithm to find patterns in the recordings, and used the instrumental variable continuous-time transfer function estimation algorithm to model them.

Results: The knee sound measurements yielded consistently lower fundamental mode decay rate in legs with meniscal tears ( 16 ±13 s ) compared to healthy legs ( 182 ±128 s ), p < 0.05. When we performed an intra-subject analysis of the injured versus contralateral legs for the 9 subjects with meniscus tears, we observed significantly lower natural frequency and damping ratio (first mode results for healthy: [Formula: see text]injured: [Formula: see text]) for the first three vibration modes (p < 0.05). These results agreed with the theoretical expectations gleaned from the vibrational model.

Significance: This combined analytical and experimental method improves our understanding of how vibrations can describe the underlying structural changes in the knee following meniscal tear, and supports their use as a tool for future efforts in non-invasively diagnosing meniscal tear injuries.
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http://dx.doi.org/10.1109/TBME.2020.3048930DOI Listing
July 2021

Transcutaneous cervical vagal nerve stimulation reduces sympathetic responses to stress in posttraumatic stress disorder: A double-blind, randomized, sham controlled trial.

Neurobiol Stress 2020 Nov 20;13:100264. Epub 2020 Oct 20.

Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA.

Objective: Exacerbated autonomic responses to acute stress are prevalent in posttraumatic stress disorder (PTSD). The purpose of this study was to assess the effects of transcutaneous cervical VNS (tcVNS) on autonomic responses to acute stress in patients with PTSD. The authors hypothesized tcVNS would reduce the sympathetic response to stress compared to a sham device.

Methods: Using a randomized double-blind approach, we studied the effects of tcVNS on physiological responses to stress in patients with PTSD (n = 25) using noninvasive sensing modalities. Participants received either sham (n = 12) or active tcVNS (n = 13) after exposure to acute personalized traumatic script stress and mental stress (public speech, mental arithmetic) over a three-day protocol. Physiological parameters related to sympathetic responses to stress were investigated.

Results: Relative to sham, tcVNS paired to traumatic script stress decreased sympathetic function as measured by: decreased heart rate (adjusted β = -5.7%; 95% CI: ±3.6%, effect size d = 0.43, p < 0.01), increased photoplethysmogram amplitude (peripheral vasodilation) (30.8%; ±28%, 0.29, p < 0.05), and increased pulse arrival time (vascular function) (6.3%; ±1.9%, 0.57, p < 0.0001). Similar (p < 0.05) autonomic, cardiovascular, and vascular effects were observed when tcVNS was applied after mental stress or without acute stress.

Conclusion: tcVNS attenuates sympathetic arousal associated with stress related to traumatic memories as well as mental stress in patients with PTSD, with effects persisting throughout multiple traumatic stress and stimulation testing days. These findings show that tcVNS has beneficial effects on the underlying neurophysiology of PTSD. Such autonomic metrics may also be evaluated in daily life settings in tandem with tcVNS therapy to provide closed-loop delivery and measure efficacy.ClinicalTrials.gov Registration # NCT02992899.
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http://dx.doi.org/10.1016/j.ynstr.2020.100264DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7739181PMC
November 2020

Towards Continuous and Ambulatory Blood Pressure Monitoring: Methods for Efficient Data Acquisition for Pulse Transit Time Estimation.

Sensors (Basel) 2020 Dec 11;20(24). Epub 2020 Dec 11.

Georgia Institute of Technology, School of Electrical and Computer Engineering, Atlanta, GA 30332, USA.

We developed a prototype for measuring physiological data for pulse transit time (PTT) estimation that will be used for ambulatory blood pressure (BP) monitoring. The device is comprised of an embedded system with multimodal sensors that streams high-throughput data to a custom Android application. The primary focus of this paper is on the hardware-software codesign that we developed to address the challenges associated with reliably recording data over Bluetooth on a resource-constrained platform. In particular, we developed a lossless compression algorithm that is based on optimally selective Huffman coding and Huffman prefixed coding, which yields virtually identical compression ratios to the standard algorithm, but with a 67-99% reduction in the size of the compression tables. In addition, we developed a hybrid software-hardware flow control method to eliminate microcontroller (MCU) interrupt-latency related data loss when multi-byte packets are sent from the phone to the embedded system via a Bluetooth module at baud rates exceeding 115,200 bit/s. The empirical error rate obtained with the proposed method with the baud rate set to 460,800 bit/s was identically equal to 0%. Our robust and computationally efficient physiological data acquisition system will enable field experiments that will drive the development of novel algorithms for PTT-based continuous BP monitoring.
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http://dx.doi.org/10.3390/s20247106DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7764444PMC
December 2020

Wearable Sensors Incorporating Compensatory Reserve Measurement for Advancing Physiological Monitoring in Critically Injured Trauma Patients.

Sensors (Basel) 2020 Nov 10;20(22). Epub 2020 Nov 10.

Georgia Institute of Technology, Atlanta, GA 30332, USA.

Vital signs historically served as the primary method to triage patients and resources for trauma and emergency care, but have failed to provide clinically-meaningful predictive information about patient clinical status. In this review, a framework is presented that focuses on potential wearable sensor technologies that can harness necessary electronic physiological signal integration with a current state-of-the-art predictive machine-learning algorithm that provides early clinical assessment of hypovolemia status to impact patient outcome. The ability to study the physiology of hemorrhage using a human model of progressive central hypovolemia led to the development of a novel machine-learning algorithm known as the compensatory reserve measurement (CRM). Greater sensitivity, specificity, and diagnostic accuracy to detect hemorrhage and onset of decompensated shock has been demonstrated by the CRM when compared to all standard vital signs and hemodynamic variables. The development of CRM revealed that continuous measurements of changes in arterial waveform features represented the most integrated signal of physiological compensation for conditions of reduced systemic oxygen delivery. In this review, detailed analysis of sensor technologies that include photoplethysmography, tonometry, ultrasound-based blood pressure, and cardiogenic vibration are identified as potential candidates for harnessing arterial waveform analog features required for real-time calculation of CRM. The integration of wearable sensors with the CRM algorithm provides a potentially powerful medical monitoring advancement to save civilian and military lives in emergency medical settings.
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http://dx.doi.org/10.3390/s20226413DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7697670PMC
November 2020

Non-Invasive Wearable Patch Utilizing Seismocardiography for Peri-Operative Use in Surgical Patients.

IEEE J Biomed Health Inform 2021 May 11;25(5):1572-1582. Epub 2021 May 11.

Objective: Optimizing peri-operative fluid management has been shown to improve patient outcomes and the use of stroke volume (SV) measurement has become an accepted tool to guide fluid therapy. The Transesophageal Doppler (TED) is a validated, minimally invasive device that allows clinical assessment of SV. Unfortunately, the use of the TED is restricted to the intra-operative setting in anesthetized patients and requires constant supervision and periodic adjustment for accurate signal quality. However, post-operative fluid management is also vital for improved outcomes. Currently, there is no device regularly used in clinics that can track patient's SV continuously and non-invasively both during and after surgery.

Methods: In this paper, we propose the use of a wearable patch mounted on the mid-sternum, which captures the seismocardiogram (SCG) and electrocardiogram (ECG) signals continuously to predict SV in patients undergoing major surgery. In a study of 12 patients, hemodynamic data was recorded simultaneously using the TED and wearable patch. Signal processing and regression techniques were used to derive SV from the signals (SCG and ECG) captured by the wearable patch and compare it to values obtained by the TED.

Results: The results showed that the combination of SCG and ECG contains substantial information regarding SV, resulting in a correlation and median absolute error between the predicted and reference SV values of 0.81 and 7.56 mL, respectively.

Significance: This work shows promise for the proposed wearable-based methodology to be used as an alternative to TED for continuous patient monitoring and guiding peri-operative fluid management.
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http://dx.doi.org/10.1109/JBHI.2020.3032938DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8189504PMC
May 2021

Estimating Knee Joint Load Using Acoustic Emissions During Ambulation.

Ann Biomed Eng 2021 Mar 9;49(3):1000-1011. Epub 2020 Oct 9.

Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.

Quantifying joint load in activities of daily life could lead to improvements in mobility for numerous people; however, current methods for assessing joint load are unsuitable for ubiquitous settings. The aim of this study is to demonstrate that joint acoustic emissions contain information to estimate this internal joint load in a potentially wearable implementation. Eleven healthy, able-bodied individuals performed ambulation tasks under varying speed, incline, and loading conditions while joint acoustic emissions and essential gait measures-electromyography, ground reaction forces, and motion capture trajectories-were collected. The gait measures were synthesized using a neuromuscular model to estimate internal joint contact force which was the target variable for subject-specific machine learning models (XGBoost) trained based on spectral, temporal, cepstral, and amplitude-based features of the joint acoustic emissions. The model using joint acoustic emissions significantly outperformed (p < 0.05) the best estimate without the sounds, the subject-specific average load (MAE = 0.31 ± 0.12 BW), for both seen (MAE = 0.08 ± 0.01 BW) and unseen (MAE = 0.21 ± 0.05 BW) conditions. This demonstrates that joint acoustic emissions contain information that correlates to internal joint contact force and that information is consistent such that unique cases can be estimated.
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http://dx.doi.org/10.1007/s10439-020-02641-7DOI Listing
March 2021

Mitigating Hypovolemia-Induced Miscalibration of Photoplethysmogram-Derived Blood Pressure.

Annu Int Conf IEEE Eng Med Biol Soc 2020 07;2020:5288-5291

Pulse transit time (PTT) is a hemodynamic indicator that may be obtained non-invasively using photoplethysmogram (PPG) signals for continuous blood pressure (BP) monitoring. Among the most promising applications of this technology are military and civilian trauma cases, where reduced blood volume due to hemorrhage, or absolute hypovolemia, is the leading preventable cause of death. However, the drawback of this method is that it requires calibration for each patient; additionally, changes in physiological state may affect PTT calibration. In this work, a porcine model (n = 6) was used to demonstrate that changes in blood volume lead to miscalibration of PTT for BP estimation. To mitigate hypovolemia-induced miscalibration, this work first defines a template-based signal quality index (SQI) for characterizing the morphology of PPG signals; it is then shown that the subject-specific calibration of SQI to BP is more robust to changes in blood volume than PTT. Though changes in PPG signal quality are not necessarily specific to changes in BP, these results suggest that PPG-based monitoring systems may benefit from incorporating morphological information for cuffless BP estimation in trauma settings.
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http://dx.doi.org/10.1109/EMBC44109.2020.9175592DOI Listing
July 2020

Cardiac Function Monitoring for Patients Undergoing Cancer Treatments Using Wearable Seismocardiography: A Proof-of-Concept Study.

Annu Int Conf IEEE Eng Med Biol Soc 2020 07;2020:4075-4078

Advances in cancer therapeutics have dramatically improved the survival rate and quality of life in patients affected by various cancers, but have been accompanied by treatment-related cardiotoxicity, e.g. left ventricular (LV) dysfunction and/or overt heart failure (HF). Cardiologists thus need to assess cancer treatment-related cardiotoxic risks and have close followups for cancer survivors and patients undergoing cancer treatments using serial echocardiography exams and cardiovascular biomarkers testing. Unfortunately, the cost-prohibitive nature of echocardiography has made these routine follow-ups difficult and not accessible to the growing number of cancer survivors and patients undergoing cancer treatments. There is thus a need to develop a wearable system that can yield similar information at a minimal cost and can be used for remote monitoring of these patients. In this proof-of-concept study, we have investigated the use of wearable seismocardiography (SCG) to monitor LV function non-invasively for patients undergoing cancer treatment. A total of 12 subjects (six with normal LV relaxation, five with impaired relaxation and one with pseudo-normal relaxation) underwent routine echocardiography followed by a standard six-minute walk test. Wearable SCG and electrocardiogram signals were collected during the six-minute walk test and, later, the signal features were compared between subjects with normal and impaired LV relaxation. Pre-ejection period (PEP) from SCG decreased significantly (p < 0.05) during exercise for the subjects with impaired relaxation compared to the subjects with normal relaxation, and changes in PEP/LV ejection time (LVET) were also significantly different between these two groups (p < 0.05). These results suggest that wearable SCG may enable monitoring of patients undergoing cancer treatments by assessing cardiotoxicity.
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http://dx.doi.org/10.1109/EMBC44109.2020.9176074DOI Listing
July 2020

Localizing Placement of Cardiomechanical Sensors during Dynamic Periods via Template Matching.

Annu Int Conf IEEE Eng Med Biol Soc 2020 07;2020:473-476

Captured with a chest-mounted sensor, the seismo- cardiogram (SCG) is a useful signal for assessing cardiomechanical function. However, the reliability of information obtained from this signal often depends upon sensor location. This has important practical implications, as consistent placement is not guaranteed in at-home and other uncontrolled settings. Building on prior research that localized SCG sensor placement when the patient was at rest - which may not be the case in practical settings - this work presents a more robust method which is able to localize sensor placement during dynamic periods, specifically exercise recovery. This was accomplished via a template-based signal quality index (SQI), which was used to infer sensor location using a variety of classifiers. While prior work generated synthetic templates for this task using an averaging method, it is shown that selecting representative templates from the training set instead enables, for the first time, SCG sensor localization during dynamic periods without patient-specific calibration. With this method, a peak accuracy of 83.32% was achieved for correctly classifying sensor position among five tested positions, with avenues for improvement of these results also presented.
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http://dx.doi.org/10.1109/EMBC44109.2020.9176732DOI Listing
July 2020

Conventional pulse transit times as markers of blood pressure changes in humans.

Sci Rep 2020 10 2;10(1):16373. Epub 2020 Oct 2.

Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI, USA.

Pulse transit time (PTT) represents a potential approach for cuff-less blood pressure (BP) monitoring. Conventionally, PTT is determined by (1) measuring (a) ECG and ear, finger, or toe PPG waveforms or (b) two of these PPG waveforms and (2) detecting the time delay between the waveforms. The conventional PTTs (cPTTs) were compared in terms of correlation with BP in humans. Thirty-two volunteers [50% female; 52 (17) (mean (SD)) years; 25% hypertensive] were studied. The four waveforms and manual cuff BP were recorded before and after slow breathing, mental arithmetic, cold pressor, and sublingual nitroglycerin. Six cPTTs were detected as the time delays between the ECG R-wave and ear PPG foot, R-wave and finger PPG foot [finger pulse arrival time (PAT)], R-wave and toe PPG foot (toe PAT), ear and finger PPG feet, ear and toe PPG feet, and finger and toe PPG feet. These time delays were also detected via PPG peaks. The best correlation by a substantial extent was between toe PAT via the PPG foot and systolic BP [- 0.63 ± 0.05 (mean ± SE); p < 0.001 via one-way ANOVA]. Toe PAT is superior to other cPTTs including the popular finger PAT as a marker of changes in BP and systolic BP in particular.
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http://dx.doi.org/10.1038/s41598-020-73143-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532447PMC
October 2020

Robust Method for Mid-Activity Tracking and Evaluation of Ankle Health Post-Injury.

IEEE Trans Biomed Eng 2021 Apr 18;68(4):1341-1350. Epub 2021 Mar 18.

Objective: To present a robust methodology for evaluating ankle health during ambulation using a wearable device. Methods: We developed a novel data capture system that leverages changes within the ankle during ambulation for real-time tracking of bioimpedance. The novel analysis compares the range of reactance at 5 kHz to the range of reactance at 100 kHz; which removes the technique's previous reliance on a known baseline. To aid in interpretation of the measurements, we developed a quantitative simulation model based on a literature review of the effects on joint bioimpedance of variations in edematous fluid volume, muscle fiber tears, and blood flow changes. Results: The results of the simulation predicted a significant difference in the ratio of the range of the reactance from 5 kHz to 100 kHz between the healthy and injured ankles. These results were validated in 15 subjects - with 11 healthy ankles and 7 injured ankles measured. The injured subjects had lateral ankle sprains 2-4 weeks prior to the measurement. The analysis technique differentiated between the healthy and the injured population (p<0.01), and a correlation (R = 0.8) with a static protocol previously validated for its sensitivity to edema. Conclusion: The technology presented can detect variations in ankle edema and structural integrity of ankles, and thus could provide valuable feedback to clinicians and patients during the rehabilitation of an ankle injury. Significance: This technology could lead to better-informed decision making regarding a patient's readiness to return to activity and / or tailoring rehabilitation activities to an individual's changing needs.
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http://dx.doi.org/10.1109/TBME.2020.3027477DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034603PMC
April 2021

Digital Cardiovascular Biomarker Responses to Transcutaneous Cervical Vagus Nerve Stimulation: State-Space Modeling, Prediction, and Simulation.

JMIR Mhealth Uhealth 2020 09 22;8(9):e20488. Epub 2020 Sep 22.

School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States.

Background: Transcutaneous cervical vagus nerve stimulation (tcVNS) is a promising alternative to implantable stimulation of the vagus nerve. With demonstrated potential in myriad applications, ranging from systemic inflammation reduction to traumatic stress attenuation, closed-loop tcVNS during periods of risk could improve treatment efficacy and reduce ineffective delivery. However, achieving this requires a deeper understanding of biomarker changes over time.

Objective: The aim of the present study was to reveal the dynamics of relevant cardiovascular biomarkers, extracted from wearable sensing modalities, in response to tcVNS.

Methods: Twenty-four human subjects were recruited for a randomized double-blind clinical trial, for whom electrocardiography and photoplethysmography were used to measure heart rate and photoplethysmogram amplitude responses to tcVNS, respectively. Modeling these responses in state-space, we (1) compared the biomarkers in terms of their predictability and active vs sham differentiation, (2) studied the latency between stimulation onset and measurable effects, and (3) visualized the true and model-simulated biomarker responses to tcVNS.

Results: The models accurately predicted future heart rate and photoplethysmogram amplitude values with root mean square errors of approximately one-fifth the standard deviations of the data. Moreover, (1) the photoplethysmogram amplitude showed superior predictability (P=.03) and active vs sham separation compared to heart rate; (2) a consistent delay of greater than 5 seconds was found between tcVNS onset and cardiovascular effects; and (3) dynamic characteristics differentiated responses to tcVNS from the sham stimulation.

Conclusions: This work furthers the state of the art by modeling pertinent biomarker responses to tcVNS. Through subsequent analysis, we discovered three key findings with implications related to (1) wearable sensing devices for bioelectronic medicine, (2) the dominant mechanism of action for tcVNS-induced effects on cardiovascular physiology, and (3) the existence of dynamic biomarker signatures that can be leveraged when titrating therapy in closed loop.

Trial Registration: ClinicalTrials.gov NCT02992899; https://clinicaltrials.gov/ct2/show/NCT02992899.

International Registered Report Identifier (irrid): RR2-10.1016/j.brs.2019.08.002.
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http://dx.doi.org/10.2196/20488DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7539162PMC
September 2020

Application of Noninvasive Vagal Nerve Stimulation to Stress-Related Psychiatric Disorders.

J Pers Med 2020 Sep 9;10(3). Epub 2020 Sep 9.

School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

Background: Vagal Nerve Stimulation (VNS) has been shown to be efficacious for the treatment of depression, but to date, VNS devices have required surgical implantation, which has limited widespread implementation.

Methods: New noninvasive VNS (nVNS) devices have been developed which allow external stimulation of the vagus nerve, and their effects on physiology in patients with stress-related psychiatric disorders can be measured with brain imaging, blood biomarkers, and wearable sensing devices. Advantages in terms of cost and convenience may lead to more widespread implementation in psychiatry, as well as facilitate research of the physiology of the vagus nerve in humans. nVNS has effects on autonomic tone, cardiovascular function, inflammatory responses, and central brain areas involved in modulation of emotion, all of which make it particularly applicable to patients with stress-related psychiatric disorders, including posttraumatic stress disorder (PTSD) and depression, since dysregulation of these circuits and systems underlies the symptomatology of these disorders.

Results: This paper reviewed the physiology of the vagus nerve and its relevance to modulating the stress response in the context of application of nVNS to stress-related psychiatric disorders.

Conclusions: nVNS has a favorable effect on stress physiology that is measurable using brain imaging, blood biomarkers of inflammation, and wearable sensing devices, and shows promise in the prevention and treatment of stress-related psychiatric disorders.
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http://dx.doi.org/10.3390/jpm10030119DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7563188PMC
September 2020

Evaluation of a Wireless Tongue Tracking System on the Identification of Phoneme Landmarks.

IEEE Trans Biomed Eng 2021 Apr 22;68(4):1190-1197. Epub 2021 Mar 22.

Objective: Evaluate the accuracy of a tongue tracking system based on the localization of a permanent magnet to generate a baseline of phoneme landmarks. The positional variability of the landmarks provides an indirect measure of the tracking errors to estimate the position of a small tracer attached on the tongue. The creation of a subject-independent (universal) baseline was also attempted for the first time.

Method: 2,500 tongue trajectories were collected from 10 subjects tasked to utter 10 repetitions of 25 phonemes. A landmark was identified from each tongue trajectory, and tracking errors were calculated by comparing the distance of each repetition landmark to a final landmark set as their mean position.

Results: In the subject-dependent baseline, the tracking errors were found to be generally consistent across all phonemes, and subjects, with less than 25% of the errors reported to be greater than 5.8 mm (median: 3.9 mm). However, the inter-subject variability showed that current limitations of our system resulted in appreciable errors (median: 55 mm, Q3: 65 mm).

Conclusion: The tracking errors reported in the subject-dependent case demonstrated the potential of our system to generate a baseline of phoneme landmarks. We have identified areas of improvement that will reduce the gap between the subject-dependent, and universal baseline, while lowering tracking errors to be comparable to the gold standard.

Significance: Creating a baseline of phoneme landmarks can help people affected by speech sound disorders to improve their intelligibility using visual feedback that guides their tongue placement to the proper position.
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http://dx.doi.org/10.1109/TBME.2020.3023284DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034549PMC
April 2021

Wearable Cuff-Less Blood Pressure Estimation at Home via Pulse Transit Time.

IEEE J Biomed Health Inform 2021 Jun 3;25(6):1926-1937. Epub 2021 Jun 3.

Objective: We developed a wearable watch-based device to provide noninvasive, cuff-less blood pressure (BP) estimation in an at-home setting.

Methods: The watch measures single-lead electrocardiogram (ECG), tri-axial seismocardiogram (SCG), and multi-wavelength photoplethysmogram (PPG) signals to compute the pulse transit time (PTT), allowing for BP estimation. We sent our custom watch device and an oscillometric BP cuff home with 21 healthy subjects, and captured the natural variability in BP over the course of a 24-hour period.

Results: After calibration, our Pearson correlation coefficient (PCC) of 0.69 and root-mean-square-error (RMSE) of 2.72 mmHg suggest that noninvasive PTT measurements correlate with around-the-clock BP. Using a novel two-point calibration method, we achieved a RMSE of 3.86 mmHg. We further demonstrated the potential of a semi-globalized adaptive model to reduce calibration requirements.

Conclusion: This is, to the best of our knowledge, the first time that BP has been comprehensively estimated noninvasively using PTT in an at-home setting. We showed a more convenient method for obtaining ambulatory BP than through the use of the standard oscillometric cuff. We presented new calibration methods for BP estimation using fewer calibration points that are more practical for a real-world scenario.

Significance: A custom watch (SeismoWatch) capable of taking multiple BP measurements enables reliable remote monitoring of daily BP and paves the way towards convenient hypertension screening and management, which can potentially reduce hospitalizations and improve quality of life.
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http://dx.doi.org/10.1109/JBHI.2020.3021532DOI Listing
June 2021

An open-source automated algorithm for removal of noisy beats for accurate impedance cardiogram analysis.

Physiol Meas 2020 08 11;41(7):075002. Epub 2020 Aug 11.

Department of Biomedical Informatics, Emory University, Atlanta, GA, United States of America. School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States of America.

Objective: The impedance cardiogram (ICG) is a non-invasive sensing modality for assessing the mechanical aspects of cardiac function, but is sensitive to artifacts from respiration, speaking, motion, and electrode displacement. Electrocardiogram (ECG)-synchronized ensemble averaging of ICG (conventional ensemble averaging method) partially mitigates these disturbances, as artifacts from intra-subject variability (ISVar) of ICG morphology and event latency remain. This paper describes an automated algorithm for removing noisy beats for improved artifact suppression in ensemble-averaged (EA) ICG beats.

Approach: Synchronized ECG and ICG signals from 144 male subjects at rest in different psychological conditions were recorded. A 'three-stage EA ICG beat' was formed by passing 60-seconds non-overlapping ECG-synchronized ICG signals through three filtering stages. The amplitude filtering stage removed spikes/noisy beats with amplitudes outside of normal physiological ranges. Cross-correlation was applied to remove noisy beats in coarse and fine filtering stages. The accuracy of the algorithm-detected artifacts was measured with expert-identified artifacts. Agreement between the expert and the algorithm was assessed using intraclass correlation coefficients (ICC) and Bland-Altman plots. The ISVar of the cardiac parameters was evaluated to quantify improvement in these estimates provided by the proposed method.

Main Results: The proposed algorithm yielded an accuracy of 96.3% and high inter-rater reliability (ICC > 0.997). Bland-Altman plots showed consistently accurate results across values. The ISVar of the cardiac parameters derived using the proposed method was significantly lower than those derived via conventional ensemble averaging method (p < 0.0001). Enhancement in resolution of fiducial points and smoothing of higher-order time derivatives of the EA ICG beats were observed.

Significance: The proposed algorithm provides a robust framework for removal of noisy beats and accurate estimation of ICG-based parameters. Importantly, the methodology reduced the ISVar of cardiac parameters. An open-source toolbox has been provided to enable other researchers to readily reproduce and improve upon this work.
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http://dx.doi.org/10.1088/1361-6579/ab9b71DOI Listing
August 2020

Enabling the assessment of trauma-induced hemorrhage via smart wearable systems.

Sci Adv 2020 Jul 22;6(30):eabb1708. Epub 2020 Jul 22.

Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

As the leading cause of trauma-related mortality, blood loss due to hemorrhage is notoriously difficult to triage and manage. To enable timely and appropriate care for patients with trauma, this work elucidates the externally measurable physiological features of exsanguination, which were used to develop a globalized model for assessing blood volume status (BVS) or the relative severity of blood loss. These features were captured via both a multimodal wearable system and a catheter-based reference and used to accurately infer BVS in a porcine model of hemorrhage ( = 6). Ultimately, high-level features of cardiomechanical function were shown to strongly predict progression toward cardiovascular collapse and used to estimate BVS with a median error of 15.17 and 18.17% for the catheter-based and wearable systems, respectively. Exploring the nexus of biomedical theory and practice, these findings lay the groundwork for digital biomarkers of hemorrhage severity and warrant further study in human subjects.
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http://dx.doi.org/10.1126/sciadv.abb1708DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7375804PMC
July 2020

A Pilot Study to Assess the Reliability of Sensing Joint Acoustic Emissions of the Wrist.

Sensors (Basel) 2020 Jul 30;20(15). Epub 2020 Jul 30.

School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30313, USA.

Joint acoustic emission (JAE) sensing has recently proven to be a viable technique for non-invasive quantification indicating knee joint health. In this work, we adapt the acoustic emission sensing method to measure the JAEs of the wrist-another joint commonly affected by injury and degenerative disease. JAEs of seven healthy volunteers were recorded during wrist flexion-extension and rotation with sensitive uniaxial accelerometers placed at eight locations around the wrist. The acoustic data were bandpass filtered (150 Hz-20 kHz). The signal-to-noise ratio (SNR) was used to quantify the strength of the JAE signals in each recording. Then, nine audio features were extracted, and the intraclass correlation coefficient (ICC) (model 3,), coefficients of variability (CVs), and Jensen-Shannon (JS) divergence were calculated to evaluate the interrater repeatability of the signals. We found that SNR ranged from 4.1 to 9.8 dB, intrasession and intersession ICC values ranged from 0.629 to 0.886, CVs ranged from 0.099 to 0.241, and JS divergence ranged from 0.18 to 0.20, demonstrating high JAE repeatability and signal strength at three locations. The volunteer sample size is not large enough to represent JAE analysis of a larger population, but this work will lay a foundation for future work in using wrist JAEs to aid in diagnosis and treatment tracking of musculoskeletal pathologies and injury in wearable systems.
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http://dx.doi.org/10.3390/s20154240DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435720PMC
July 2020

The Delineation of Fiducial Points for Non-Contact Radar Seismocardiogram Signals Without Concurrent ECG.

IEEE J Biomed Health Inform 2021 Apr 6;25(4):1031-1040. Epub 2021 Apr 6.

Objective: Non-contact sensing of seismocardiogram (SCG) signals through a microwave Doppler radar is promising for biomedical applications. However, the delineation of fiducial points for radar SCG still relies on concurrent ECG which requires a contact sensor and limits the complete non-contact detection of SCG.

Methods: Instead of ECG, a new reference signal, the radar displacement signal of heartbeat (RDH), was derived through the complex Fourier transform and the band pass filtering of the radar signal. The RDH signal was used to locate each cardiac cycle and mask the systolic profile, which was further used to detect an important fiducial point, aortic valve opening (AO). The beat-to-beat interval was estimated from AO-AO interval and compared with the gold standard, ECG R-to-R interval.

Results: For the 22 subjects in the study, the evaluation of the AOs detected by RDH (AO) shows the average detection ratio can reach 90%, indicating a high ratio of the AO that are exactly the same as AO detected using the ECG R-wave (AO). Additionally, the left ventricular ejection time (LVET) values estimated from the ensemble averaged radar waveform through AO segmentation are within 2 ms of those through AO segmentation, for all the detected subjects. Further analysis demonstrates that the beat-to-beat intervals calculated from AO have an average root-mean-square-deviation (RMSD) of 53.73 ms when compared with ECG R-to-R intervals, and have an average RMSD of 23.47 ms after removing the beats in which AO cannot be identified.

Conclusions: Radar signal RDH can be used as a reference signal to delineate fiducial points for non-contact radar SCG signals.

Significance: This study can be applied to develop complete non-contact sensing of SCG and monitoring of vital signs, where contact-based SCG is not feasible.
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http://dx.doi.org/10.1109/JBHI.2020.3009997DOI Listing
April 2021

Estimation of Instantaneous Oxygen Uptake During Exercise and Daily Activities Using a Wearable Cardio-Electromechanical and Environmental Sensor.

IEEE J Biomed Health Inform 2021 Mar 5;25(3):634-646. Epub 2021 Mar 5.

Objective: To estimate instantaneous oxygen uptake VO with a small, low-cost wearable sensor during exercise and daily activities in order to enable monitoring of energy expenditure (EE) in uncontrolled settings. We aim to do so using a combination of seismocardiogram (SCG), electrocardiogram (ECG) and atmospheric pressure (AP) signals obtained from a minimally obtrusive wearable device.

Methods: In this study, subjects performed a treadmill protocol in a controlled environment and an outside walking protocol in an uncontrolled environment. During testing, the COSMED K5 metabolic system collected gold standard breath-by-breath (BxB) data and a custom-built wearable patch placed on the mid-sternum collected SCG, ECG and AP signals. We extracted features from these signals to estimate the BxB VO data obtained from the COSMED system.

Results: In estimating instantaneous VO, we achieved our best results on the treadmill protocol using a combination of SCG (frequency) and AP features (RMSE of 3.68 ± 0.98 ml/kg/min and R of 0.77). For the outside protocol, we achieved our best results using a combination of SCG (frequency), ECG and AP features (RMSE of 4.3 ± 1.47 ml/kg/min and R of 0.64). In estimating VO consumed over one minute intervals during the protocols, our median percentage error was 15.8[Formula: see text] for the treadmill protocol and 20.5[Formula: see text] for the outside protocol.

Conclusion: SCG, ECG and AP signals from a small wearable patch can enable accurate estimation of instantaneous VO in both controlled and uncontrolled settings. SCG signals capturing variation in cardio-mechanical processes, AP signals, and state of the art machine learning models contribute significantly to the accurate estimation of instantaneous VO.

Significance: Accurate estimation of VO with a low cost, minimally obtrusive wearable patch can enable the monitoring of VO and EE in everyday settings and make the many applications of these measurements more accessible to the general public.
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http://dx.doi.org/10.1109/JBHI.2020.3009903DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8004550PMC
March 2021

Harnessing the Manifold Structure of Cardiomechanical Signals for Physiological Monitoring During Hemorrhage.

IEEE Trans Biomed Eng 2021 Jun 21;68(6):1759-1767. Epub 2021 May 21.

Objective: Local oscillation of the chest wall in response to events during the cardiac cycle may be captured using a sensing modality called seismocardiography (SCG), which is commonly used to infer cardiac time intervals (CTIs) such as the pre-ejection period (PEP). An important factor impeding the ubiquitous application of SCG for cardiac monitoring is that morphological variability of the signals makes consistent inference of CTIs a difficult task in the time-domain. The goal of this work is therefore to enable SCG-based physiological monitoring during trauma-induced hemorrhage using signal dynamics rather than morphological features.

Methods: We introduce and explore the observation that SCG signals follow a consistent low-dimensional manifold structure during periods of changing PEP induced in a porcine model of trauma injury. Furthermore, we show that the distance traveled along this manifold correlates strongly to changes in PEP ( ∆PEP).

Results: ∆PEP estimation during hemorrhage was achieved with a median R of 92.5% using a rapid manifold approximation method, comparable to an ISOMAP reference standard, which achieved an R of 95.3%.

Conclusion: Rapidly approximating the manifold structure of SCG signals allows for physiological inference abstracted from the time-domain, laying the groundwork for robust, morphology-independent processing methods.

Significance: Ultimately, this work represents an important advancement in SCG processing, enabling future clinical tools for trauma injury management.
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http://dx.doi.org/10.1109/TBME.2020.3014040DOI Listing
June 2021

Fit to Burst: Toward Noninvasive Estimation of Achilles Tendon Load Using Burst Vibrations.

IEEE Trans Biomed Eng 2021 Feb 21;68(2):470-481. Epub 2021 Jan 21.

Objective: Tendons are essential components of the musculoskeletal system and, as with any mechanical structure, can fail under load. Tendon injuries are common and can be debilitating, and research suggests that a better understanding of their loading conditions could help mitigate injury risk and improve rehabilitation. To that end, we present a novel method of noninvasively assessing parameters related to mechanical load in the Achilles tendon using burst vibrations.

Methods: These vibrations, produced by a small vibration motor on the skin superficial to the tendon, are sensed by a skin-mounted accelerometer, which measures the tendon's response to burst excitation under varying tensile load. In this study, twelve healthy subjects performed a variety of everyday tasks designed to expose the Achilles tendon to a range of loading conditions. To approximate the vibration motor-tendon system and provide an explanation for observed changes in tendon response, a 2-degree-of-freedom mechanical systems model was developed.

Results: Reliable, characteristic changes in the burst response profile as a function of Achilles tendon tension were observed during all loading tasks. Using a machine learning-based approach, we developed a regression model capable of accurately estimating net ankle moment-which captures general trends in tendon tension-across a range of walking speeds and across subjects (R = 0.85). Simulated results of the mechanical model accurately recreated behaviors observed in vivo. Finally, preliminary, proof-of-concept results from a fully wearable system demonstrated trends similar to those observed in experiments conducted using benchtop equipment.

Conclusion: These findings suggest that an untethered, unobtrusive system can effectively assess tendon loading during activities of daily life.

Significance: Access to such a system would have broad implications for injury recovery and prevention, athletic training, and the study of human movement.
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http://dx.doi.org/10.1109/TBME.2020.3005353DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7875505PMC
February 2021

Vibration Characterization of the Human Knee Joint in Audible Frequencies.

Sensors (Basel) 2020 Jul 25;20(15). Epub 2020 Jul 25.

School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30308, USA.

Injuries and disorders affecting the knee joint are very common in athletes and older individuals. Passive and active vibration methods, such as acoustic emissions and modal analysis, are extensively used in both industry and the medical field to diagnose structural faults and disorders. To maximize the diagnostic potential of such vibration methods for knee injuries and disorders, a better understanding of the vibroacoustic characteristics of the knee must be developed. In this study, the linearity and vibration transmissibility of the human knee were investigated based on measurements collected on healthy subjects. Different subjects exhibit a substantially different transmissibility behavior due to variances in subject-specific knee structures. Moreover, the vibration behaviors of various subjects' knees at different leg positions were compared. Variation in sagittal-plane knee angle alters the transmissibility of the joint, while the overall shape of the transmissibility diagrams remains similar. The results demonstrate that an adjusted stimulation signal at frequencies higher than 3 kHz has the potential to be employed in diagnostic applications that are related to knee joint health. This work can pave the way for future studies aimed at employing acoustic emission and modal analysis approaches for knee health monitoring outside of clinical settings, such as for field-deployable diagnostics.
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http://dx.doi.org/10.3390/s20154138DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7436205PMC
July 2020

Non-invasive vagal nerve stimulation decreases brain activity during trauma scripts.

Brain Stimul 2020 Sep - Oct;13(5):1333-1348. Epub 2020 Jul 10.

Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA; Department of Radiology, Emory University School of Medicine, Atlanta, GA, USA; Atlanta VA Medical Center, Decatur, GA, USA.

Background: Traumatic stress can have lasting effects on neurobiology and result in psychiatric conditions such as posttraumatic stress disorder (PTSD). We hypothesize that non-invasive cervical vagal nerve stimulation (nVNS) may alleviate trauma symptoms by reducing stress sympathetic reactivity. This study examined how nVNS alters neural responses to personalized traumatic scripts.

Methods: Nineteen participants who had experienced trauma but did not have the diagnosis of PTSD completed this double-blind sham-controlled study. In three sequential time blocks, personalized traumatic scripts were presented to participants immediately followed by either sham stimulation (n = 8; 0-14 V, 0.2 Hz, pulse width = 5s) or active nVNS (n = 11; 0-30 V, 25 Hz, pulse width = 40 ms). Brain activity during traumatic scripts was assessed using High Resolution Positron Emission Tomography (HR-PET) with radiolabeled water to measure brain blood flow.

Results: Traumatic scripts resulted in significant activations within the bilateral medial and orbital prefrontal cortex, premotor cortex, anterior cingulate, thalamus, insula, hippocampus, right amygdala, and right putamen. Greater activation was observed during sham stimulation compared to nVNS within the bilateral prefrontal and orbitofrontal cortex, premotor cortex, temporal lobe, parahippocampal gyrus, insula, and left anterior cingulate. During the first exposure to the trauma scripts, greater activations were found in the motor cortices and ventral visual stream whereas prefrontal cortex and anterior cingulate activations were more predominant with later script presentations for those subjects receiving sham stimulation.

Conclusion: nVNS decreases neural reactivity to an emotional stressor in limbic and other brain areas involved in stress, with changes over repeated exposures suggesting a shift from scene appraisal to cognitively processing the emotional event.
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http://dx.doi.org/10.1016/j.brs.2020.07.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8214872PMC
March 2021

A Wearable System for Attenuating Essential Tremor Based on Peripheral Nerve Stimulation.

IEEE J Transl Eng Health Med 2020 6;8:2000111. Epub 2020 Apr 6.

School of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaGA30332USA.

Objective: Currently available treatments for kinetic tremor can cause intolerable side effects or be highly invasive and expensive. Even though several studies have shown the positive effects of external feedback (i.e., electrical stimulation) for suppressing tremor, such approaches have not been fully integrated into wearable real-time feedback systems.

Method: We have developed a wireless wearable stimulation system that analyzes upper limb tremor using a three-axis accelerometer and that modulates/attenuates tremor using peripheral-nerve electrical stimulation with adjustable stimulation parameters and a real-time tremor detection algorithm. We outfitted nine subjects with tremor with a wearable system and a set of surface electrodes placed on the skin overlying the radial nerve and tested the effects of stimulation with nine combinations of parameters for open- and closed-loop stimulation on tremor. To quantify the effects of the stimulation, we measured tremor movements, and analyzed the dominant tremor frequency and tremor power.

Results: Baseline tremor power gradually decreased over the course of 18 stimulation trials. During the last trial, compared with the control trial, the reduction rate of tremor power was 42.17 ± 3.09%. The dominant tremor frequency could be modulated more efficiently by phase-locked closed-loop stimulation. The tremor power was equally reduced by open- and closed-loop stimulation.

Conclusion: Peripheral nerve stimulation significantly affects tremor, and stimulation parameters need to be optimized to modulate tremor metrics. Clinical Impact: This preliminary study lays the foundation for future studies that will evaluate the efficacy of the proposed closed-loop peripheral nerve stimulation method in a larger group of patients with kinetic tremor.
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http://dx.doi.org/10.1109/JTEHM.2020.2985058DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7313727PMC
April 2020