@article{roy_zheng_kamper_hu_2023, title={Concurrent and Continuous Prediction of Finger Kinetics and Kinematics via Motoneuron Activities}, volume={70}, ISSN={["1558-2531"]}, DOI={10.1109/TBME.2022.3232067}, abstractNote={Objective: Robust neural decoding of intended motor output is crucial to enable intuitive control of assistive devices, such as robotic hands, to perform daily tasks. Few existing neural decoders can predict kinetic and kinematic variables simultaneously. The current study developed a continuous neural decoding approach that can concurrently predict fingertip forces and joint angles of multiple fingers. Methods: We obtained motoneuron firing activities by decomposing high-density electromyogram (HD EMG) signals of the extrinsic finger muscles. The identified motoneurons were first grouped and then refined specific to each finger (index or middle) and task (finger force and dynamic movement) combination. The refined motoneuron groups (separate matrix) were then applied directly to new EMG data in real-time involving both finger force and dynamic movement tasks produced by both fingers. EMG-amplitude-based prediction was also performed as a comparison. Results: We found that the newly developed decoding approach outperformed the EMG-amplitude method for both finger force and joint angle estimations with a lower prediction error (Force: 3.47±0.43 vs 6.64±0.69% MVC, Joint Angle: 5.40±0.50° vs 12.8±0.65°) and a higher correlation (Force: 0.75±0.02 vs 0.66±0.05, Joint Angle: 0.94±0.01 vs 0.5±0.05) between the estimated and recorded motor output. The performance was also consistent for both fingers. Conclusion: The developed neural decoding algorithm allowed us to accurately and concurrently predict finger forces and joint angles of multiple fingers in real-time. Significance: Our approach can enable intuitive interactions with assistive robotic hands, and allow the performance of dexterous hand skills involving both force control tasks and dynamic movement control tasks.}, number={6}, journal={IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING}, author={Roy, Rinku and Zheng, Yang and Kamper, Derek G. G. and Hu, Xiaogang}, year={2023}, month={Jun}, pages={1911–1920} }
 @article{zheng_shin_kamper_hu_2021, title={Automatic Detection of Contracting Muscle Regions via the Deformation Field of Transverse Ultrasound Images: A Feasibility Study}, volume={49}, ISSN={["1573-9686"]}, DOI={10.1007/s10439-020-02557-2}, abstractNote={Accurate identification of contracting muscles can help us to understand the muscle function in both physiological and pathological conditions. Conventional electromyography (EMG) have limited access to deep muscles, crosstalk, or instability in the recordings. Accordingly, a novel framework was developed to detect contracting muscle regions based on the deformation field of transverse ultrasound images. We first estimated the muscle movements in a stepwise calculation, to derive the deformation field. We then calculated the divergence of the deformation field to locate the expanding or shrinking regions during muscle contractions. Two preliminary experiments were performed to evaluate the feasibility of the developed algorithm. Using concurrent intramuscular EMG recordings, Experiment I verified that the divergence map can capture the activity of superficial and deep muscles, when muscles were activated voluntarily or through electrical stimulation. Experiment II verified that the divergence map can only capture contracting muscles but not muscle shortening during passive movements. The results demonstrated that the divergence can individually capture the activity of muscles at different depths, and was not sensitive to muscle shortening during passive movements. The proposed framework can automatically detect the regions of contracting muscle, and could potentially serve as a tool to assess the functions of a group of muscles concurrently.}, number={1}, journal={ANNALS OF BIOMEDICAL ENGINEERING}, author={Zheng, Yang and Shin, Henry and Kamper, Derek G. and Hu, Xiaogang}, year={2021}, month={Jan}, pages={354–366} }
 @article{zheng_hu_2021, title={Concurrent Prediction of Finger Forces Based on Source Separation and Classification of Neuron Discharge Information}, volume={31}, ISSN={["1793-6462"]}, DOI={10.1142/S0129065721500106}, abstractNote={ A reliable neural-machine interface is essential for humans to intuitively interact with advanced robotic hands in an unconstrained environment. Existing neural decoding approaches utilize either discrete hand gesture-based pattern recognition or continuous force decoding with one finger at a time. We developed a neural decoding technique that allowed continuous and concurrent prediction of forces of different fingers based on spinal motoneuron firing information. High-density skin-surface electromyogram (HD-EMG) signals of finger extensor muscle were recorded, while human participants produced isometric flexion forces in a dexterous manner (i.e. produced varying forces using either a single finger or multiple fingers concurrently). Motoneuron firing information was extracted from the EMG signals using a blind source separation technique, and each identified neuron was further classified to be associated with a given finger. The forces of individual fingers were then predicted concurrently by utilizing the corresponding motoneuron pool firing frequency of individual fingers. Compared with conventional approaches, our technique led to better prediction performances, i.e. a higher correlation ([Formula: see text] versus [Formula: see text]), a lower prediction error ([Formula: see text]% MVC versus [Formula: see text]% MVC), and a higher accuracy in finger state (rest/active) prediction ([Formula: see text]% versus [Formula: see text]%). Our decoding method demonstrated the possibility of classifying motoneurons for different fingers, which significantly alleviated the cross-talk issue of EMG recordings from neighboring hand muscles, and allowed the decoding of finger forces individually and concurrently. The outcomes offered a robust neural-machine interface that could allow users to intuitively control robotic hands in a dexterous manner. }, number={06}, journal={INTERNATIONAL JOURNAL OF NEURAL SYSTEMS}, author={Zheng, Yang and Hu, Xiaogang}, year={2021}, month={Jun} }
 @article{xu_zheng_hu_2021, title={Estimation of Joint Kinematics and Fingertip Forces using Motoneuron Firing Activities: A Preliminary Report}, ISSN={["1948-3546"]}, DOI={10.1109/NER49283.2021.9441433}, abstractNote={A loss of individuated finger movement affects critical aspects of daily activities. There is a need to develop neural-machine interface techniques that can continuously decode single finger movements. In this preliminary study, we evaluated a novel decoding method that used finger-specific motoneuron firing frequency to estimate joint kinematics and fingertip forces. High-density electromyogram (EMG) signals were obtained during which index or middle fingers produced either dynamic flexion movements or isometric flexion forces. A source separation method was used to extract motor unit (MU) firing activities from a single trial. A separate validation trial was used to only retain the MUs associated with a particular finger. The finger-specific MU firing activities were then used to estimate individual finger joint angles and isometric forces in a third trial using a regression method. Our results showed that the MU firing based approach led to smaller prediction errors for both joint angles and forces compared with the conventional EMG amplitude based method. The outcomes can help develop intuitive neural-machine interface techniques that allow continuous single-finger level control of robotic hands. In addition, the previously obtained MU separation information was applied directly to new data, and it is therefore possible to enable online extraction of MU firing activities for real-time neural-machine interactions.}, journal={2021 10TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER)}, author={Xu, Feng and Zheng, Yang and Hu, Xiaogang}, year={2021}, pages={1035–1038} }
 @article{zheng_hu_2020, title={Elicited upper limb motions through transcutaneous cervical spinal cord stimulation}, volume={17}, ISSN={["1741-2552"]}, DOI={10.1088/1741-2552/ab8f6f}, abstractNote={Objective. Transcutaneous cervical spinal cord stimulation (tsCSC) has been demonstrated to activate the dorsal root and activate targeted muscles. However, it is unclear whether tsCSC can elicit functionally relevant movements of the upper limb for assistive/rehabilitative purposes. Approach. The current study sought to elicit arm and hand movements by tsCSC by placing an electrode array near the cervical segments of the spinal cord. Anode stimulation current pulses were delivered to the dorsal side at 120 Hz and 30 Hz in separate trials. The elicited joint kinematics were captured using a motion tracking system. Main results. The results revealed that distal and proximal joint movements can be elicited either independently or synergistically. Specifically, different motions, including flexion and extension of the elbow, wrist, and five digits, can be selectively elicited by adjusting the stimulation parameters, such as stimulation location and stimulation intensity. Significance. The findings demonstrated the feasibility of the spinal cord stimulation technique in eliciting functional movements of the upper limb. The outcomes also revealed the potential of the tsCSC technique as a promising assistive or rehabilitative method for individuals with impaired function of the upper limb.}, number={3}, journal={JOURNAL OF NEURAL ENGINEERING}, author={Zheng, Yang and Hu, Xiaogang}, year={2020}, month={Jun} }
 @article{zheng_hu_2020, title={Muscle activation pattern elicited through transcutaneous stimulation near the cervical spinal cord}, volume={17}, ISSN={["1741-2552"]}, DOI={10.1088/1741-2552/ab5e09}, abstractNote={Objective. Neuromuscular electrical stimulation can help activate muscles of individuals with neurological disorders. However, conventional electrical stimulation targets distal branches of motor axons, and activates muscles non-physiologically. For example, stimulation at the muscle belly activates muscles in a highly synchronized manner. Accordingly, we investigated whether the muscle activation pattern was more asynchronized through transcutaneous stimulation near the cervical spinal cord (tsCSC). Approach. A stimulation array was placed on the posterior side near the cervical spinal cord, to target the arm and hand muscles. Stimulation trains of 10 Hz and 30 Hz were delivered. Electromyogram signals were recorded to quantify the muscle activation patterns. Arm and finger joint kinematics were also recorded using a motion capture system. Main results. After an initial synchronized activation prior to 35 ms after stimulation onset, we observed substantial asynchronized muscle activities with a long latency (>35 ms). The asynchronized activation is also more evident in distal muscles compared with the proximal muscles. In addition, the decreased synchronization level of muscle activities correlated with a reduced fluctuation of joint movement. The highly asynchronized muscle activities indicated an activation of the sensory axons and/or dorsal roots as well as a possible involvement of some spinal-supraspinal circuitry. Significance. Our tsCSC approach can improve the muscle activation pattern during electrical stimulation with a possible involvement of the spinal and supraspinal pathways, which can facilitate applications on rehabilitation/assistance of individuals with impaired motor function.}, number={1}, journal={JOURNAL OF NEURAL ENGINEERING}, author={Zheng, Yang and Hu, Xiaogang}, year={2020}, month={Feb} }
 @article{zheng_hu_2019, title={Elicited Finger and Wrist Extension Through Transcutaneous Radial Nerve Stimulation}, volume={27}, ISSN={["1558-0210"]}, DOI={10.1109/TNSRE.2019.2930669}, abstractNote={Individuals with neurological disorders, such as stroke or spinal cord injury, often have weakness and/or spasticity in their hand and wrist muscles, which can lead to impaired ability to extend their fingers and wrists. Functional electrical stimulation can help to restore these motor functions. However, the conventional stimulation method can lead to fast muscle fatigue and limited movements due to a non-physiological recruitment of motor units and a limited recruitment of deep muscles. In this paper, we investigated the feasibility of eliciting various hand opening and wrist extension movement patterns through a transcutaneous electrical stimulation array, which targeted the proximal segment of the radial nerve bundle proximal to the elbow. The wrist and finger joint kinematics were used to classify the different movement patterns through a cluster analysis, and electromyogram signals from the wrist and finger extensors were recorded to investigate the muscle activation patterns. The results showed that the finger and wrist motions can be elicited both independently and in a coordinated manner, by changing the stimulation intensity and stimulation location. H-reflex activity was also observed, which demonstrated the potential of recruiting motor units in a physiological order. Our approach could be further developed into a rehabilitative/assistive tool for individuals with impaired hand opening and/or wrist extension.}, number={9}, journal={IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING}, author={Zheng, Yang and Hu, Xiaogang}, year={2019}, month={Sep}, pages={1875–1882} }
 @article{zheng_vukina_zheng_2019, title={Estimating asymmetric information effects in health care with uninsurable costs}, volume={19}, ISSN={["2199-9031"]}, DOI={10.1007/s10754-018-9246-z}, abstractNote={We use a structural approach to separately estimate moral hazard and adverse selection effects in health care utilization using hospital invoices data. Our model explicitly accounts for the heterogeneity in the non-insurable transactions costs associated with hospital visits which increase the individuals' total cost of health care and dampen the moral hazard effect. A measure of moral hazard is derived as the difference between the observed and the counterfactual health care consumption. In the population of patients with non life-threatening diagnoses, our results indicate statistically significant and economically meaningful moral hazard. We also test for the presence of adverse selection by investigating whether patients with different health status sort themselves into different health insurance plans. Adverse selection is confirmed in the data because patients with estimated worse health tend to buy the insurance coverage and patients with estimated better health choose not to buy the insurance coverage.}, number={1}, journal={INTERNATIONAL JOURNAL OF HEALTH ECONOMICS AND MANAGEMENT}, author={Zheng, Yan and Vukina, Tomislav and Zheng, Xiaoyong}, year={2019}, month={Mar}, pages={79–98} }
 @article{zheng_hu_2019, title={Interference Removal From Electromyography Based on Independent Component Analysis}, volume={27}, ISSN={["1558-0210"]}, DOI={10.1109/TNSRE.2019.2910387}, abstractNote={High-density surface electromyography (HD-EMG) provides detailed information about muscle activation. However, HD-EMG recordings can be interfered by motion artifacts and power line noise. In this paper, an interference detection and removal method with minimal distortion of the EMG was developed based on the independent component analysis (ICA). After the source separation, the independent components with power line noise were detected based on the spectra and were processed with notch filters. Components with motion artifacts were identified by analyzing the peak frequency of the spectrum, and motion artifacts were filtered with a high-pass filter and an amplitude thresholding method. The EMG signals were then reconstructed based on the processed source signals. The denoising performance was evaluated on both simulated and experimental EMG signals. The results showed that our method was significantly better than the digital filter method and the conventional ICA-based method where components with interferences were set to zero. Namely, our method showed a minimal distortion of the denoised EMG amplitude and frequency and a higher yield of decomposed motor units. Our interference detection and removal algorithm can be used as an effective preprocessing procedure and can benefit macro level EMG analysis and micro level motor unit analysis.}, number={5}, journal={IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING}, author={Zheng, Yang and Hu, Xiaogang}, year={2019}, month={May}, pages={887–894} }
 @article{zheng_lu_polash_rasoulianboroujeni_liu_manley_deng_sun_chen_hermann_et al._2019, title={Paramagnon drag in high thermoelectric figure of merit Li-doped MnTe}, volume={5}, ISSN={["2375-2548"]}, url={https://doi.org/10.1126/sciadv.aat9461}, DOI={10.1126/sciadv.aat9461}, abstractNote={Neutrons spot magnetic fluctuations that propel charges in a novel class of paramagnetic thermoelectrics.}, number={9}, journal={SCIENCE ADVANCES}, publisher={American Association for the Advancement of Science (AAAS)}, author={Zheng, Y. and Lu, T. and Polash, Md M. H. and Rasoulianboroujeni, M. and Liu, N. and Manley, M. E. and Deng, Y. and Sun, P. J. and Chen, X. L. and Hermann, R. P. and et al.}, year={2019}, month={Sep} }
 @article{zheng_hu_2019, title={Real-time isometric finger extension force estimation based on motor unit discharge information}, volume={16}, ISSN={["1741-2552"]}, DOI={10.1088/1741-2552/ab2c55}, abstractNote={Objective. The goal of this study was to perform real-time estimation of isometric finger extension force using the discharge information of motor units (MUs). Approach. A real-time electromyogram (EMG) decomposition method based on the fast independent component analysis (FastICA) algorithm was developed to extract MU discharge events from high-density (HD) EMG recordings. The decomposition was first performed offline during an initialization period, and the obtained separation matrix was then applied to new data samples in real-time. Since MU pool discharge probability reflects the neural drive to spinal motoneurons, individual finger forces were estimated based on a firing rate-force model established during the initialization, termed the neural-drive method. The conventional EMG amplitude-based method was used to estimate the forces as a comparison, termed the EMG-amplitude method. Simulated HD-EMG signals were first used to evaluate the accuracy of the real-time decomposition. Experimental EMG recordings of 5 min of isometric finger extension with pseudorandom force levels were used to assess the performance of force estimation over time. Main results. The simulation results showed that the accuracy of real-time decomposition was 86%, compared with an offline accuracy of 94%. However, the real-time decomposition accuracy was stable over time. The experimental results showed that the neural-drive method had a significantly smaller root mean square error (RMSE) of the force estimation compared with the EMG-amplitude method, which was consistent across fingers. Additionally, the RMSE of the neural-drive method was stable until 230 s, while the RMSE of the EMG-amplitude method increased progressively over time. Significance. The neural-drive method on real-time finger force estimation was more accurate over time compared with the conventional EMG-amplitude method during prolonged muscle contractions. The outcomes can potentially offer a more accurate and robust neural interface technique for reliable neural-machine interactions based on MU pool discharge information.}, number={6}, journal={JOURNAL OF NEURAL ENGINEERING}, author={Zheng, Yang and Hu, Xiaogang}, year={2019}, month={Dec} }
 @article{zheng_hu_2018, title={Improved muscle activation using proximal nerve stimulation with subthreshold current pulses at kilohertz-frequency}, volume={15}, ISSN={["1741-2552"]}, DOI={10.1088/1741-2552/aab90f}, abstractNote={Objective. Transcutaneous electrical nerve stimulation can help individuals with neurological disorders to regain their motor function by activating muscles externally. However, conventional stimulation technique often induces near-simultaneous recruitment of muscle fibers, leading to twitch forces time-locked to the stimulation. Approach. To induce less synchronized activation of finger flexor muscles, we delivered clustered narrower pulses to the proximal segment of the median and ulnar nerves at a carrier frequency of either 10 kHz (with an 80 µs pulse width) or 7.14 kHz (with a 120 µs pulse width) (high-frequency mode, HF), and different clustered pulses were delivered at a frequency of 30 or 40 Hz. Conventional stimulation with pulse frequency of 30 or 40 Hz (low-frequency mode, LF) was used for comparison. With matched elicited muscle forces between the HF and LF modes, the force variation, the high-density electromyogram (EMG) signals recorded at the finger flexor muscles and stimulation-induced-pain levels were compared. Main results. The compound action potentials in the 10 kHz HF mode revealed a significant difference (i.e. a lower amplitude and area, and a wider duration) compared with the LF mode, indicating cancellations of asynchronized action potentials. A smaller fluctuation in the elicited forces in the 10 kHz mode further demonstrated the less synchronized activation of different motor units. These effects tended to be weaker in the 7.14 kHz HF condition. However, the levels of pain sensation was not reduced in the HF mode potentially due to the high charge density used in the HF mode. Our findings indicated that different nerve fibers were recruited asynchronously through summations of different numbers of subthreshold depolarizations in the HF mode. Significance. Compared with the LF mode, the HF mode stimulation was capable of activating the nerve fibers in a less synchronized way, which is more similar to the physiological activation pattern.}, number={4}, journal={JOURNAL OF NEURAL ENGINEERING}, author={Zheng, Yang and Hu, Xiaogang}, year={2018}, month={Aug} }
 @article{zheng_shin_hu_2018, title={Muscle Fatigue Post-stroke Elicited From Kilohertz-Frequency Subthreshold Nerve Stimulation}, volume={9}, ISSN={["1664-2295"]}, DOI={10.3389/fneur.2018.01061}, abstractNote={Purpose: Rapid muscle fatigue limits clinical applications of functional electrical stimulation (FES) for individuals with motor impairments. This study aimed to characterize the sustainability of muscle force elicited with a novel transcutaneous nerve stimulation technique. Method: A hemiplegic chronic stroke survivor was recruited in this case study. Clustered subthreshold pulses of 60-μs with kilohertz (12.5 kHz) carrier frequency (high-frequency mode, HF) were delivered transcutaneously to the proximal segment of the median/ulnar nerve bundles to evaluate the finger flexor muscle fatigue on both sides of the stroke survivor. Conventional nerve stimulation technique with 600-μs pulses at 30 Hz (low-frequency mode, LF) served as the control condition. Fatigue was evoked by intermittently delivering 3-s stimulation trains with 1-s resting. For fair comparison, initial contraction forces (approximately 30% of the maximal voluntary contraction) were matched between the HF and LF modes. Muscle fatigue was evaluated through elicited finger flexion forces (amplitude and fluctuation) and muscle activation patterns quantified by high-density electromyography (EMG). Result: Compared with those from the LF stimuli, the elicited forces declined more slowly, and the force plateau was higher under the HF stimulation for both the affected and contralateral sides, resulting in a more sustainable force output at higher levels. Meanwhile, the force fluctuation under the HF stimulation increased more slowly, and, thus, was smaller after successive stimulation trains compared with the LF stimuli, indicating a less synchronized activation of muscle fibers. The efficiency of the muscle activation, measured as the force-EMG ratio, was also higher in the HF stimulation mode. Conclusion: Our results indicated that the HF nerve stimulation technique can reduce muscle fatigue in stroke survivors by maintaining a higher efficiency of muscle activations compared with the LF stimulation. The technique can help improve the performance of neurorehabilitation methods based on electrical stimulation, and facilitate the utility of FES in clinical populations.}, journal={FRONTIERS IN NEUROLOGY}, author={Zheng, Yang and Shin, Henry and Hu, Xiaogang}, year={2018}, month={Dec} }
 @article{zheng_hu_2018, title={Reduced muscle fatigue using kilohertz-frequency subthreshold stimulation of the proximal nerve}, volume={15}, ISSN={["1741-2552"]}, DOI={10.1088/1741-2552/aadecc}, abstractNote={Objective. Conventional electrical stimulation techniques targeting the motor points often induce early muscle fatigue onset that can limit clinical applications. In our current study, we evaluated the muscle activation and force generation during fatigue using a novel stimulation technique. Approach. Clustered subthreshold 80 μs current pulses at 10 kHz (high-frequency mode, HF) were delivered transcutaneously to activate the median and ulnar nerve bundles and induce dispersed activations of motor units. Conventional stimulation technique with 800 μs pulses at 30 Hz (low-frequency mode, LF) served as a control condition. Fatigue was evoked by delivering the stimuli continuously for 5 min, with matched initial contraction force (approximately 30% of maximal voluntary contraction) between the HF and LF modes. The elicited finger flexion forces and the muscle activation patterns quantified by high-density electromyogram (EMG) from the finger flexor muscles were compared. Main results. Our results revealed that the elicited force was prolonged under the HF stimulation mode, manifested as a slower decay of the force, a smaller absolute force decline, a higher force plateau, and a larger force-time integral, in comparison with the LF mode. The force-to-EMG ratio under the HF stimulation was also consistently higher than that under the LF mode. In addition, the EMG spatial distribution showed that the muscle activation tended to be more spread-out under the HF mode compared with the LF mode. These results indicated that the HF stimulation induced a higher efficiency of muscle activation, which can potentially reduce muscle fatigue. Significance. Our findings revealed that the subthreshold kilohertz nerve stimulation can induce temporally and spatially dispersed activation of different motor units with more efficient activation patterns. The reduced muscle fatigue can have a prominent advantage in neural rehabilitation involving transcutaneous electrical nerve stimulations.}, number={6}, journal={JOURNAL OF NEURAL ENGINEERING}, author={Zheng, Yang and Hu, Xiaogang}, year={2018}, month={Dec} }