{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T22:41:07Z","timestamp":1770676867400,"version":"3.49.0"},"reference-count":28,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2021,11,18]],"date-time":"2021-11-18T00:00:00Z","timestamp":1637193600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Digital technologies provide the opportunity to analyze gait patterns in patients with Parkinson\u2019s Disease using wearable sensors in clinical settings and a home environment. Confirming the technical validity of inertial sensors with a 3D motion capture system is a necessary step for the clinical application of sensor-based gait analysis. Therefore, the objective of this study was to compare gait parameters measured by a mobile sensor-based gait analysis system and a motion capture system as the gold standard. Gait parameters of 37 patients were compared between both systems after performing a standardized 5 \u00d7 10 m walking test by reliability analysis using intra-class correlation and Bland\u2013Altman plots. Additionally, gait parameters of an age-matched healthy control group (n = 14) were compared to the Parkinson cohort. Gait parameters representing bradykinesia and short steps showed excellent reliability (ICC &gt; 0.96). Shuffling gait parameters reached ICC &gt; 0.82. In a stridewise synchronization, no differences were observed for gait speed, stride length, stride time, relative stance and swing time (p &gt; 0.05). In contrast, heel strike, toe off and toe clearance significantly differed between both systems (p &lt; 0.01). Both gait analysis systems distinguish Parkinson patients from controls. Our results indicate that wearable sensors generate valid gait parameters compared to the motion capture system and can consequently be used for clinically relevant gait recordings in flexible environments.<\/jats:p>","DOI":"10.3390\/s21227680","type":"journal-article","created":{"date-parts":[[2021,11,19]],"date-time":"2021-11-19T02:43:09Z","timestamp":1637289789000},"page":"7680","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":60,"title":["Validation of a Sensor-Based Gait Analysis System with a Gold-Standard Motion Capture System in Patients with Parkinson\u2019s Disease"],"prefix":"10.3390","volume":"21","author":[{"given":"Verena","family":"Jakob","sequence":"first","affiliation":[{"name":"Movement and Gait Lab, Sana-Krankenhaus Rummelsberg, 90592 Schwarzenbruck, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5686-281X","authenticated-orcid":false,"given":"Arne","family":"K\u00fcderle","sequence":"additional","affiliation":[{"name":"Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), 91052 Erlangen, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4921-6104","authenticated-orcid":false,"given":"Felix","family":"Kluge","sequence":"additional","affiliation":[{"name":"Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), 91052 Erlangen, Germany"}]},{"given":"Jochen","family":"Klucken","sequence":"additional","affiliation":[{"name":"Digital Medicine, University of Luxembourg, 4365 Esch-sur-Alzette, Luxembourg"},{"name":"Digital Medicine, Luxembourg Institute of Health, 1445 Strassen, Luxembourg"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0417-0336","authenticated-orcid":false,"given":"Bjoern M.","family":"Eskofier","sequence":"additional","affiliation":[{"name":"Machine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), 91052 Erlangen, Germany"}]},{"given":"J\u00fcrgen","family":"Winkler","sequence":"additional","affiliation":[{"name":"Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), 91054 Erlangen, Germany"}]},{"given":"Martin","family":"Winterholler","sequence":"additional","affiliation":[{"name":"Department of Neurology, Sana-Krankenhaus Rummelsberg, 90592 Schwarzenbruck, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2037-9460","authenticated-orcid":false,"given":"Heiko","family":"Gassner","sequence":"additional","affiliation":[{"name":"Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander Universit\u00e4t Erlangen-N\u00fcrnberg (FAU), 91054 Erlangen, Germany"},{"name":"Fraunhofer IIS, Fraunhofer Institute for Integrated Circuits IIS, 91058 Erlangen, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"471","DOI":"10.3389\/fneur.2019.00471","article-title":"Alteration of tremor dominant and postural instability gait difficulty subtypes during the progression of Parkinson\u2019s disease: Analysis of the PPMI cohort","volume":"10","author":"Lee","year":"2019","journal-title":"Front. Neurol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1007\/s00115-014-4084-9","article-title":"Gangst\u00f6rungen im Alter (Gait disorders in the elderly)","volume":"85","author":"Amadori","year":"2014","journal-title":"Der Nervenarzt"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1763","DOI":"10.3233\/JPD-202129","article-title":"Clinical relevance of standardized mobile gait tests. Reliability analysis between gait recordings at hospital and home in Parkinson\u2019s disease: A pilot study","volume":"10","author":"Sanders","year":"2020","journal-title":"J. Parkinson\u2019s Dis."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.ijge.2013.03.005","article-title":"Gait disorders in Parkinson\u2019s disease: Assessment and management","volume":"7","author":"Chen","year":"2013","journal-title":"Int. J. Gerontol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"7729","DOI":"10.4081\/ni.2018.7729","article-title":"Quantitative assessment of gait parameters in people with Parkinson\u2019s disease in laboratory and clinical setting: Are the measures interchangeable?","volume":"10","author":"Pau","year":"2018","journal-title":"Neurol. Int."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"G\u00f6tz-Neumann, K. (2016). Gehen Verstehen: Ganganalyse in der Physiotherapie, Thieme. [4th ed.].","DOI":"10.1055\/b-003-127005"},{"key":"ref_7","unstructured":"Perry, J., and Burnfield, J. (2010). Gait Analysis\u2014Normal and Pathological Function, SLACK Incorporated. [2nd ed.]."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Eskofier, B., Lee, S., Baron, M., Simon, A., Martindale, C., Ga\u00dfner, H., and Klucken, J. (2017). An overview of smart shoes in the internet of health things: Gait and mobility assessment in health promotion and disease monitoring. Appl. Sci., 7.","DOI":"10.3390\/app7100986"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1293","DOI":"10.1002\/mds.26718","article-title":"Free-living monitoring of Parkinson\u2019s disease: Les-sons from the field","volume":"31","author":"Godfrey","year":"2016","journal-title":"Mov. Disord."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Klucken, J., Barth, J., Kugler, P., Schlachetzki, J., Henze, T., Marxreiter, F., Kohl, Z., Steidl, R., Hornegger, J., and Eskofier, B. (2013). Unbiased and mobile gait analysis detects motor impairment in Parkinson\u2019s disease. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0056956"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"5","DOI":"10.3389\/fneur.2019.00005","article-title":"The diagnostic scope of sensor-based gait analysis in atypical parkinsonism: Further observations","volume":"10","author":"Raccagni","year":"2019","journal-title":"Front. Neurol."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Schlachetzki, J.C.M., Barth, J., Marxreiter, F., Gossler, J., Kohl, Z., Reinfelder, S., Gassner, H., Aminian, K., Eskofier, B.M., and Winkler, J. (2017). Wearable sensors objectively measure gait parameters in Parkinson\u2019s disease. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0183989"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Kluge, F., Ga\u00dfner, H., Hannink, J., Pasluosta, C., Klucken, J., and Eskofier, B.M. (2017). Towards mobile gait analysis: Concurrent validity and test-retest reliability of an inertial measurement system for the assessment of spatio-temporal gait parameters. Sensors, 17.","DOI":"10.3390\/s17071522"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1050","DOI":"10.1002\/mds.26256","article-title":"In-patient multidisciplinary rehabilitation for Parkinson\u2019s disease: A randomized controlled trial","volume":"30","author":"Monticone","year":"2015","journal-title":"Mov. Disord."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1011","DOI":"10.1002\/mds.26277","article-title":"Multidisciplinary rehabilitation in Parkinson\u2019s disease: A mile-stone with future challenges","volume":"30","author":"Rochester","year":"2015","journal-title":"Mov. Disord."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"828","DOI":"10.1136\/jnnp-2017-316437","article-title":"Efficacy of intensive multidisciplinary rehabilitation in Parkinson\u2019s disease: A randomised controlled study","volume":"89","author":"Ferrazzoli","year":"2018","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1136\/jnnp.55.3.181","article-title":"Accuracy of clinical diagnosis of idiopathic Parkinson\u2019s disease: A clinico-pathological study of 100 cases","volume":"55","author":"Hughes","year":"1992","journal-title":"J. Neurol. Neurosurg. Psychiatry"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"6419","DOI":"10.3390\/s150306419","article-title":"Stride segmentation during free walk movements using multi-dimensional subsequence dynamic time warping on inertial sensor data","volume":"15","author":"Barth","year":"2015","journal-title":"Sensors"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1089","DOI":"10.1109\/TBME.2014.2368211","article-title":"Inertial sensor-based stride parameter calculation from gait sequences in geriatric patients","volume":"62","author":"Rampp","year":"2015","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"550","DOI":"10.3389\/fneur.2017.00550","article-title":"Gait and cognition in Parkinson\u2019s disease: Cognitive impairment is inadequately reflected by gait performance during dual task","volume":"8","author":"Marxreiter","year":"2017","journal-title":"Front. Neurol."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Kanzler, C.M., Barth, J., Rampp, A., Schlarb, H., Rott, F., Klucken, J., and Eskofier, B.M. (2015, January 25\u201329). Inertial sensor based and shoe size independent gait analysis including heel and toe clearance estimation. Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan, Italy.","DOI":"10.1109\/EMBC.2015.7319618"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Baudet, A., Morisset, C., d\u2019Athis, P., Maillefert, J.-F., Casillas, J.-M., Ornetti, P., and Laroche, D. (2014). Cross-talk correction method for knee kinematics in gait analysis using principal component analysis (PCA): A new proposal. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0102098"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1757-1146-1-S1-O28","article-title":"Use of the Oxford Foot Model in clinical practice","volume":"1","author":"McCahill","year":"2008","journal-title":"J. Foot. Ankle. Res."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3162","DOI":"10.1109\/TBME.2012.2216263","article-title":"Heel and toe clearance estimation for gait analysis using wireless inertial sensors","volume":"59","author":"Mariani","year":"2012","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.jcm.2016.02.012","article-title":"A guideline of selecting and reporting intraclass correlation coefficients for reliability research","volume":"15","author":"Koo","year":"2016","journal-title":"J. Chiropr. Med."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"28","DOI":"10.11138\/FNeur\/2017.32.1.028","article-title":"Gait analysis and clinical correlations in early Parkinson\u2019s disease","volume":"32","author":"Pistacchi","year":"2017","journal-title":"Funct. Neurol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1186\/s12984-019-0548-2","article-title":"Development and clinical validation of inertial sensor-based gait-clustering methods in Parkinson\u2019s disease","volume":"16","author":"Nguyen","year":"2019","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1272","DOI":"10.1002\/mds.26642","article-title":"Technology in Parkinson\u2019s disease: Challenges and opportunities","volume":"31","author":"Espay","year":"2016","journal-title":"Mov. Disord."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/22\/7680\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:32:25Z","timestamp":1760167945000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/22\/7680"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,18]]},"references-count":28,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["s21227680"],"URL":"https:\/\/doi.org\/10.3390\/s21227680","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,18]]}}}