{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:29:46Z","timestamp":1760239786821,"version":"build-2065373602"},"reference-count":40,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2020,12,21]],"date-time":"2020-12-21T00:00:00Z","timestamp":1608508800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100013699","name":"Bundesministerium f\u00fcr Bildung, Wissenschaft und Forschung","doi-asserted-by":"publisher","award":["FKZ: 13GW0122E and FKZ: 01DN18011A"],"award-info":[{"award-number":["FKZ: 13GW0122E and FKZ: 01DN18011A"]}],"id":[{"id":"10.13039\/501100013699","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Wearable devices play an increasing role in the rehabilitation of patients with movement disorders. Although information about muscular activation is highly interesting, no approach exists that allows reliable collection of this information when the sensor is applied autonomously by the patient. This paper aims to demonstrate the proof-of-principle of an innovative sEMG sensor system, which can be used intuitively by patients while detecting their muscular activation with sufficient accuracy. The sEMG sensor system utilizes a multichannel approach based on 16 sEMG leads arranged circularly around the limb. Its design enables a stable contact between the skin surface and the system\u2019s dry electrodes, fulfills the SENIAM recommendations regarding the electrode size and inter-electrode distance and facilitates a high temporal resolution. The proof-of-principle was demonstrated by elbow flexion\/extension movements of 10 subjects, proving that it has root mean square values and a signal-to-noise ratio comparable to commercial systems based on pre-gelled electrodes. Furthermore, it can be easily placed and removed by patients with reduced arm function and without detailed knowledge about the exact positioning of the sEMG electrodes. With its features, the demonstration of the sEMG sensor system\u2019s proof-of-principle positions it as a wearable device that has the potential to monitor muscular activation in home and community settings.<\/jats:p>","DOI":"10.3390\/s20247348","type":"journal-article","created":{"date-parts":[[2020,12,21]],"date-time":"2020-12-21T09:41:41Z","timestamp":1608543701000},"page":"7348","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Introduction of a sEMG Sensor System for Autonomous Use by Inexperienced Users"],"prefix":"10.3390","volume":"20","author":[{"given":"Elisa","family":"Romero Avila","sequence":"first","affiliation":[{"name":"Department of Rehabilitation &amp; Prevention Engineering, Institute of Applied Medical Engineering, RWTH Aachen University, Pauwelsstr. 20, 52074 Aachen, Germany"}]},{"given":"Elmar","family":"Junker","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation &amp; Prevention Engineering, Institute of Applied Medical Engineering, RWTH Aachen University, Pauwelsstr. 20, 52074 Aachen, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7624-6961","authenticated-orcid":false,"given":"Catherine","family":"Disselhorst-Klug","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation &amp; Prevention Engineering, Institute of Applied Medical Engineering, RWTH Aachen University, Pauwelsstr. 20, 52074 Aachen, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1186\/1743-0003-9-21","article-title":"A review of wearable sensors and systems with application in rehabilitation","volume":"9","author":"Patel","year":"2012","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1186\/s12984-019-0610-0","article-title":"JNER at 15 years: Analysis of the state of neuroengineering and rehabilitation","volume":"16","author":"Reinkensmeyer","year":"2019","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1186\/s12984-019-0559-z","article-title":"Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling","volume":"16","author":"Durandau","year":"2019","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Vincent, C., Deaudelin, I., Robichaud, L., Rousseau, J., Viscogliosi, C., Talbot, L.R., Desrosiers, J., and Group, B. (2007). Rehabilitation needs for older adults with stroke living at home: Perceptions of four populations. BMC Geriatr., 7.","DOI":"10.1186\/1471-2318-7-20"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Cotton, R.J., and Rogers, J. (2019). Wearable Monitoring of Joint Angle and Muscle Activity. 2019 IEEE 16th International Conference on Rehabilitation Robotics, IEEE.","DOI":"10.1109\/ICORR.2019.8779538"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1340","DOI":"10.1016\/j.apmr.2006.06.006","article-title":"Validity of accelerometry for monitoring real-world arm activity in patients with subacute stroke: Evidence from the extremity constraint-induced therapy evaluation trial","volume":"87","author":"Uswatte","year":"2006","journal-title":"Arch. Phys. Med. Rehabil."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1109\/JPROC.2009.2038727","article-title":"A Novel Approach to Monitor Rehabilitation Outcomes in Stroke Survivors Using Wearable Technology","volume":"98","author":"Patel","year":"2010","journal-title":"Proc. IEEE"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1177\/1545968310374189","article-title":"A Novel Approach to Ambulatory Monitoring: Investigation into the Quantity and Control of Everyday Walking in Patients with Subacute Stroke","volume":"25","author":"Prajapati","year":"2011","journal-title":"Neurorehabil. Neural Repair"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"do Nascimento, L.M.S., Bonfati, L.V., Freitas, M.L., Mendes, J.J.A., Siqueira, H.V., and Stevan, S.L. (2020). Sensors and Systems for Physical Rehabilitation and Health Monitoring\u2014A Review. Sensors, 20.","DOI":"10.3390\/s20154063"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3","DOI":"10.3389\/fneur.2018.01122","article-title":"Editorial: Electromyography (EMG) Techniques for the Assessment and Rehabilitation of Motor Impairment Following Stroke","volume":"9","author":"Klein","year":"2018","journal-title":"Front. Neurol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1109\/RBME.2012.2183586","article-title":"Accessing the neural drive to muscle and translation to neurorehabilitation technologies","volume":"5","author":"Farina","year":"2012","journal-title":"IEEE Rev. Biomed. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1109\/TNSRE.2009.2036615","article-title":"A Combined sEMG and Accelerometer System for Monitoring Functional Activity in Stroke","volume":"17","author":"Roy","year":"2009","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Pereira, A., Folgado, D., Nunes, F., Almeida, J., and Sousa, I. (2019). Using Inertial Sensors to Evaluate Exercise Correctness in Electromyography-Based Home Rehabilitation Systems, IEEE.","DOI":"10.1109\/MeMeA.2019.8802152"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Campanini, I., Disselhorst-Klug, C., Rymer, W.Z., and Merletti, R. (2020). Surface EMG in Clinical Assessment and Neurorehabilitation: Barriers Limiting Its Use. Front. Neurol., 11.","DOI":"10.3389\/fneur.2020.00934"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1109\/TNSRE.2014.2305111","article-title":"The Extraction of Neural Information from the Surface EMG for the Control of Upper-Limb Prostheses: Emerging Avenues and Challenges","volume":"22","author":"Farina","year":"2014","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1186\/s12984-019-0565-1","article-title":"Perspectives of people with spinal cord injury learning to walk using a powered exoskeleton","volume":"16","author":"Manns","year":"2019","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.clinbiomech.2008.08.006","article-title":"Technology and instrumentation for detection and conditioning of the surface electromyographic signal: State of the art","volume":"24","author":"Merletti","year":"2009","journal-title":"Clin. Biomech."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S1050-6411(01)00033-5","article-title":"Sampling, noise-reduction and amplitude estimation issues in surface electromyography","volume":"12","author":"Clancy","year":"2002","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"5","DOI":"10.3389\/fneur.2017.00107","article-title":"Advanced Myoelectric Control for Robotic Hand-Assisted Training: Outcome from a Stroke Patient","volume":"8","author":"Lu","year":"2017","journal-title":"Front. Neurol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1109\/TNSRE.2016.2560906","article-title":"Development of an EMG-ACC-Based Upper Limb Rehabilitation Training System","volume":"25","author":"Liu","year":"2017","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"C\u00f4t\u00e9-Allard, U., Gagnon-Turcotte, G., Laviolette, F., and Gosselin, B. (2019). A Low-Cost, Wireless, 3-D-Printed Custom Armband for sEMG Hand Gesture Recognition. Sensors, 19.","DOI":"10.3390\/s19122811"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Yamagami, M., Peters, K.M., Milovanovic, I., Kuang, I., Yang, Z., Lu, N., and Steele, K.M. (2018). Assessment of Dry Epidermal Electrodes for Long-Term Electromyography Measurements. Sensors, 18.","DOI":"10.3390\/s18041269"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Zhao, S.M., Liu, J.X., Gong, Z.D., Lei, Y.S., OuYang, X., Chan, C.C., and Ruan, S.C. (2020). Wearable Physiological Monitoring System Based on Electrocardiography and Electromyography for Upper Limb Rehabilitation Training. Sensors, 20.","DOI":"10.3390\/s20174861"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Li, J., Wang, P., and Huang, H.J. (2020). Dry Epidermal Electrodes Can Provide Long-Term High Fidelity Electromyography for Limited Dynamic Lower Limb Movements. Sensors, 20.","DOI":"10.3390\/s20174848"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1007\/BF02442444","article-title":"Influences of electrode geometry on bipolar recordings of surface electromyogram","volume":"16","author":"Lynn","year":"1978","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/S1050-6411(97)00043-6","article-title":"Variability of some SEMG parameter estimates with electrode location","volume":"8","author":"Hogrel","year":"1998","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1016\/j.jelekin.2006.06.001","article-title":"Effect of electrode location on EMG signal envelope in leg muscles during gait","volume":"17","author":"Campanini","year":"2007","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1016\/j.jelekin.2008.07.006","article-title":"Surface EMG: The issue of electrode location","volume":"19","author":"Mesin","year":"2009","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1016\/j.bspc.2015.02.009","article-title":"Current state of digital signal processing in myoelectric interfaces and related applications","volume":"18","author":"Hakonen","year":"2015","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.jelekin.2019.07.008","article-title":"Consensus for experimental design in electromyography (CEDE) project: Electrode selection matrix","volume":"48","author":"Besomi","year":"2019","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"489","DOI":"10.3390\/s120100489","article-title":"A Wireless sEMG Recording System and Its Application to Muscle Fatigue Detection","volume":"12","author":"Chang","year":"2012","journal-title":"Sensors"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.jht.2019.12.021","article-title":"Advances in motion and electromyography based wearable technology for upper extremity function rehabilitation: A review","volume":"33","author":"Sethi","year":"2020","journal-title":"J. Hand Ther."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.jelekin.2019.102363","article-title":"Tutorial. Surface EMG detection in space and time: Best practices","volume":"49","author":"Merletti","year":"2019","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1016\/j.jbiomech.2011.11.010","article-title":"Inter-electrode spacing of surface EMG sensors: Reduction of crosstalk contamination during voluntary contractions","volume":"45","author":"Kuznetsov","year":"2012","journal-title":"J. Biomech."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/S1050-6411(00)00027-4","article-title":"Development of recommendations for SEMG sensors and sensor placement procedures","volume":"10","author":"Hermens","year":"2000","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Disselhorst-Klug, C., and Williams, S. (2020). Surface Electromyography Meets Biomechanics: Correct Interpretation of sEMG-Signals in Neuro-Rehabilitation Needs Biomechanical Input. Front. Neurol., 11.","DOI":"10.3389\/fneur.2020.603550"},{"key":"ref_37","first-page":"25","article-title":"Technical Features and Functionalities of Myo Armband: An Overview on Related Literature and Advanced Applications of Myoelectric Armbands Mainly Focused on Arm Prostheses","volume":"11","author":"Visconti","year":"2018","journal-title":"Int. J. Smart Sens. Intell. Syst."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.jelekin.2016.03.004","article-title":"The role of biceps brachii and brachioradialis for the control of elbow flexion and extension movements","volume":"28","year":"2016","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.clinbiomech.2008.08.003","article-title":"Surface electromyography and muscle force: Limits in sEMG-force relationship and new approaches for applications","volume":"24","author":"Rau","year":"2009","journal-title":"Clin. Biomech."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1803","DOI":"10.1152\/jappl.1995.79.5.1803","article-title":"Automatic assessment of electromyogram quality","volume":"79","author":"Sinderby","year":"1995","journal-title":"J. Appl. Physiol."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/24\/7348\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:48:02Z","timestamp":1760179682000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/24\/7348"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,21]]},"references-count":40,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2020,12]]}},"alternative-id":["s20247348"],"URL":"https:\/\/doi.org\/10.3390\/s20247348","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2020,12,21]]}}}