{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T05:08:26Z","timestamp":1772082506462,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T00:00:00Z","timestamp":1674432000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004329","name":"Slovenian Research Agency","doi-asserted-by":"publisher","award":["P2-0228"],"award-info":[{"award-number":["P2-0228"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Patients after stroke need to re-learn functional movements required for independent living throughout the rehabilitation process. In the study, we used a wearable sensory system for monitoring the movement of the upper limbs while performing activities of daily living. We implemented time-based and path-based segmentation of movement trajectories and muscle activity to quantify the activities of the unaffected and the affected upper limbs. While time-based segmentation splits the trajectory in quants of equal duration, path-based segmentation isolates completed movements. We analyzed the hand movement path and forearm muscle activity and introduced a bimanual movement parameter, which enables differentiation between unimanual and bimanual activities. The approach was validated in a study that included a healthy subject and seven patients after stroke with different levels of disabilities. Path-based segmentation provides a more detailed and comprehensive evaluation of upper limb activities, while time-based segmentation is more suitable for real-time assessment and providing feedback to patients. Bimanual movement parameter effectively differentiates between different levels of upper limb involvement and is a clear indicator of the activity of the affected limb relative to the unaffected limb.<\/jats:p>","DOI":"10.3390\/s23031289","type":"journal-article","created":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T03:26:41Z","timestamp":1674444401000},"page":"1289","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Time-Based and Path-Based Analysis of Upper-Limb Movements during Activities of Daily Living"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0979-652X","authenticated-orcid":false,"given":"Sebastjan","family":"\u0160lajpah","sequence":"first","affiliation":[{"name":"Faculty of Electrical Engineering, University of Ljubljana, Tr\u017ea\u0161ka cesta 25, 1000 Ljubljana, Slovenia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eva","family":"\u010ceba\u0161ek","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering, University of Ljubljana, Tr\u017ea\u0161ka cesta 25, 1000 Ljubljana, Slovenia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5289-4059","authenticated-orcid":false,"given":"Marko","family":"Munih","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering, University of Ljubljana, Tr\u017ea\u0161ka cesta 25, 1000 Ljubljana, Slovenia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2563-7094","authenticated-orcid":false,"given":"Matja\u017e","family":"Mihelj","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering, University of Ljubljana, Tr\u017ea\u0161ka cesta 25, 1000 Ljubljana, Slovenia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1693","DOI":"10.1016\/S0140-6736(11)60325-5","article-title":"Stroke rehabilitation","volume":"377","author":"Langhorne","year":"2011","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"892","DOI":"10.1056\/NEJMra001529","article-title":"Cardiac rehabilitation and secondary prevention of coronary heart disease","volume":"345","author":"Ades","year":"2001","journal-title":"N. Engl. J. Med."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1002\/oti.277","article-title":"A review of bilateral training for upper extremity hemiparesis","volume":"16","author":"Stoykov","year":"2009","journal-title":"Occup. Ther. Int."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Tognetti, A., Lorussi, F., Carbonaro, N., De Rossi, D., De Toma, G., Mancuso, C., Paradiso, R., Luinge, H., Reenalda, J., and Droog, E. (2014, January 26\u201330). Daily-life monitoring of stroke survivors motor performance: The interaction sensing system. Proceedings of the 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Chicago, IL, USA.","DOI":"10.1109\/EMBC.2014.6944525"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1109\/TITB.2007.899496","article-title":"Detection of daily activities and sports with wearable sensors in controlled and uncontrolled conditions","volume":"12","author":"Ermes","year":"2008","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1088\/0967-3334\/37\/3\/442","article-title":"Wavelet-based algorithm for auto-detection of daily living activities of older adults captured by multiple inertial measurement units (IMUs)","volume":"37","author":"Ayachi","year":"2016","journal-title":"Physiol. Meas."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.gaitpost.2016.06.008","article-title":"The feasibility of shoulder motion tracking during activities of daily living using inertial measurement units","volume":"49","author":"Kirking","year":"2016","journal-title":"Gait Posture"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Lemmens, R.J., Janssen-Potten, Y.J., Timmermans, A.A., Smeets, R.J., and Seelen, H.A. (2015). Recognizing complex upper extremity activities using body worn sensors. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0118642"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Faria, D.R., and Dias, J. (2009, January 11\u201315). 3D hand trajectory segmentation by curvatures and hand orientation for classification through a probabilistic approach. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, USA.","DOI":"10.1109\/IROS.2009.5354792"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1186\/1743-0003-11-133","article-title":"Infant trunk posture and arm movement assessment using pressure mattress, inertial and magnetic measurement units (IMUs)","volume":"11","author":"Rihar","year":"2014","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_11","unstructured":"Wang, H., Su, H., Zheng, K., Sadiq, S., and Zhou, X. (February, January 29). An effectiveness study on trajectory similarity measures. Proceedings of the Twenty-Fourth Australasian Database Conference, Adelaide, Australia."},{"key":"ref_12","unstructured":"Eiter, T., and Mannila, H. (1994). Computing Discrete Fr\u00e9chet Distance, Citeseer. Technical Report."},{"key":"ref_13","first-page":"405","article-title":"A review of vision based hand gestures recognition","volume":"2","author":"Murthy","year":"2009","journal-title":"Int. J. Inf. Technol. Knowl. Manag."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"864","DOI":"10.1002\/aic.690440412","article-title":"Synchronization of batch trajectories using dynamic time warping","volume":"44","author":"Kassidas","year":"1998","journal-title":"AIChE J."},{"key":"ref_15","unstructured":"Laurinen, P., Siirtola, P., and R\u00f6ning, J. (2006, January 13\u201316). Efficient Algorithm for Calculating Similarity between Trajectories Containing an Increasing Dimension. Proceedings of the 24th IASTED International Conference on Artificial Intelligence and Applications, Innsbruck, Austria."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3362","DOI":"10.3390\/s140203362","article-title":"Gait analysis methods: An overview of wearable and non-wearable systems, highlighting clinical applications","volume":"14","year":"2014","journal-title":"Sensors"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2255","DOI":"10.3390\/s120202255","article-title":"Gait analysis using wearable sensors","volume":"12","author":"Tao","year":"2012","journal-title":"Sensors"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1192","DOI":"10.1109\/SURV.2012.110112.00192","article-title":"A survey on human activity recognition using wearable sensors","volume":"15","author":"Lara","year":"2013","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.bspc.2015.09.001","article-title":"Spectral Collaborative Representation based Classification for hand gestures recognition on electromyography signals","volume":"24","author":"Boyali","year":"2016","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1682\/JRRD.2010.09.0177","article-title":"Electromyogram pattern recognition for control of powered upper-limb prostheses: State-of-the-art and challenges for clinical use","volume":"48","author":"Scheme","year":"2011","journal-title":"J. Rehabil. Res. Dev."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1251\/bpo115","article-title":"Techniques of EMG signal analysis: Detection, processing, classification and applications","volume":"8","author":"Reaz","year":"2006","journal-title":"Biol. Proced. Online"},{"key":"ref_22","unstructured":"Sathiyanarayanan, M., Mulling, T., and Nazir, B. (2015). Controlling a Robot Using a Wearable Device (MYO). Int. J. Eng. Dev. Res., 3."},{"key":"ref_23","unstructured":"Abduo, M., and Galster, M. (2015). MYO Gesture Control Armband for Medical Applications, University of Canterbury."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Huang, D., Zhang, X., Saponas, T.S., Fogarty, J., and Gollakota, S. (2015, January 8\u201311). Leveraging dual-observable input for fine-grained thumb interaction using forearm EMG. Proceedings of the 28th Annual ACM Symposium on User Interface Software and Technology, Charlotte, NC, USA.","DOI":"10.1145\/2807442.2807506"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Wahab, A., Lam, C., and Sundaraj, K. (2016, January 28\u201330). Analysis and Classification of Forearm Muscles Activities during Gripping using EMG Signals. Proceedings of the 3rd International Conference on Movement, Health and Exercise, Malacca, Malaysia.","DOI":"10.1007\/978-981-10-3737-5_18"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"11933","DOI":"10.3390\/s120911933","article-title":"A highly miniaturized, wireless inertial measurement unit for characterizing the dynamics of pitched baseballs and softballs","volume":"12","author":"McGinnis","year":"2012","journal-title":"Sensors"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2501","DOI":"10.1109\/TIM.2012.2187360","article-title":"Three-axial accelerometer calibration using Kalman filter covariance matrix for online estimation of optimal sensor orientation","volume":"61","author":"Beravs","year":"2012","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"109966","DOI":"10.1016\/j.measurement.2021.109966","article-title":"Measurement of multimodal physiological signals for stimulation detection by wearable devices","volume":"184","author":"Cosoli","year":"2021","journal-title":"Measurement"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1939","DOI":"10.1007\/s42114-022-00525-z","article-title":"Multifunctional wearable strain\/pressure sensor based on conductive carbon nanotubes\/silk nonwoven fabric with high durability and low detection limit","volume":"5","author":"He","year":"2022","journal-title":"Adv. Compos. Hybrid Mater."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2008936","DOI":"10.1002\/adfm.202008936","article-title":"Wearable sensors-enabled human\u2013machine interaction systems: From design to application","volume":"31","author":"Yin","year":"2021","journal-title":"Adv. Funct. Mater."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Repnik, E., Puh, U., Goljar, N., Munih, M., and Mihelj, M. (2018). Using Inertial Measurement Units and Electromyography to Quantify Movement during Action Research Arm Test Execution. Sensors, 18.","DOI":"10.3390\/s18092767"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"4645","DOI":"10.1073\/pnas.96.8.4645","article-title":"Quantization of continuous arm movements in humans with brain injury","volume":"96","author":"Krebs","year":"1999","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Ude, A., Vuga, R., Nemec, B., and Morimoto, J. (2016, January 9\u201314). Trajectory representation by nonlinear scaling of dynamic movement primitives. Proceedings of the 2016 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Republic of Korea.","DOI":"10.1109\/IROS.2016.7759695"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"349","DOI":"10.3758\/BF03195388","article-title":"Measuring daily behavior using ambulatory accelerometry: The Activity Monitor","volume":"33","author":"Bussmann","year":"2001","journal-title":"Behav. Res. Methods Instrum. Comput."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2493","DOI":"10.1161\/01.STR.0000185928.90848.2e","article-title":"Reliability and validity of the upper-extremity Motor Activity Log-14 for measuring real-world arm use","volume":"36","author":"Uswatte","year":"2005","journal-title":"Stroke"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1097\/NPT.0b013e31806748bd","article-title":"Upper extremity use in people with hemiparesis in the first few weeks after stroke","volume":"31","author":"Lang","year":"2007","journal-title":"J. Neurol. Phys. Ther."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1009","DOI":"10.1589\/jpts.26.1009","article-title":"Comparison of upper extremity motor recovery of stroke patients with actual physical activity in their daily lives measured with accelerometers","volume":"26","author":"Shim","year":"2014","journal-title":"J. Phys. Ther. Sci."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Bailey, R.R., Klaesner, J.W., and Lang, C.E. (2014). An accelerometry-based methodology for assessment of real-world bilateral upper extremity activity. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0103135"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1177\/1545968315583720","article-title":"Quantifying real-world upper-limb activity in nondisabled adults and adults with chronic stroke","volume":"29","author":"Bailey","year":"2015","journal-title":"Neurorehabilit. Neural Repair"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1017\/BrImp.2015.21","article-title":"Exploring the role of accelerometers in the measurement of real world upper-limb use after stroke","volume":"17","author":"Hayward","year":"2016","journal-title":"Brain Impair."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1437","DOI":"10.1016\/j.apmr.2011.02.021","article-title":"Assessment of arm activity using triaxial accelerometry in patients with a stroke","volume":"92","author":"Verbunt","year":"2011","journal-title":"Arch. Phys. Med. Rehabil."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1007\/BF02348122","article-title":"Ambulatory measurement of upper limb usage and mobility-related activities during normal daily life with an upper limb-activity monitor: A feasibility study","volume":"40","author":"Schasfoort","year":"2002","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1016\/j.apmr.2004.04.049","article-title":"Continuous monitoring of upper-limb activity in a free-living environment","volume":"86","author":"Granat","year":"2005","journal-title":"Arch. Phys. Med. Rehabil."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"van Meulen, F.B., van Beijnum, B.J.F., Buurke, J.H., and Veltink, P.H. (2017, January 17\u201320). Assessment of lower arm movements using one inertial sensor. Proceedings of the 2017 International Conference on Rehabilitation Robotics (ICORR), London, UK.","DOI":"10.1109\/ICORR.2017.8009445"},{"key":"ref_45","first-page":"210","article-title":"Objective evaluation of the quality of movement in daily life after stroke","volume":"3","author":"Klaassen","year":"2016","journal-title":"Front. Bioeng. Biotechnol."},{"key":"ref_46","unstructured":"Montgomery, D.C., and Runger, G.C. (2010). Applied Statistics and Probability for Engineers, John Wiley & Sons."},{"key":"ref_47","unstructured":"Dumitrescu, A., and Rote, G. (2004, January 9\u201311). On the Fr\u00e9chet distance of a set of curves. Proceedings of the 16th Canadian Conference on Computational Geometry (CCCG), Montreal, QC, Canada."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/3\/1289\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:13:55Z","timestamp":1760120035000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/3\/1289"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,23]]},"references-count":47,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["s23031289"],"URL":"https:\/\/doi.org\/10.3390\/s23031289","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,23]]}}}