{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T12:22:29Z","timestamp":1764937349079,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2021,12,10]],"date-time":"2021-12-10T00:00:00Z","timestamp":1639094400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"publisher","award":["P20GM103447"],"award-info":[{"award-number":["P20GM103447"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This study is motivated by the fact that there are currently no widely used applications available to quantitatively measure a power wheelchair user\u2019s mobility, which is an important indicator of quality of life. To address this issue, we propose an approach that allows power wheelchair users to use their own mobile devices, e.g., a smartphone or smartwatch, to non-intrusively collect mobility data in their daily life. However, the convenience of data collection brings substantial challenges in data analysis because the data patterns associated with wheelchair maneuvers are not as strong as other activities, e.g., walking, running, etc. In addition, the built-in sensors in different mobile devices create significant heterogeneity in terms of sensitivity, noise patterns, sampling settings, etc. To address the aforementioned challenges, we developed a novel approach composed of algorithms that work collaboratively to reduce noise, identify patterns intrinsic to wheelchair maneuvers, and finalize mobility analysis by removing spikes and dips caused by abrupt maneuver changes. We conducted a series of experiments to evaluate the proposed approach. Experimental results showed that our approach could accurately determine wheelchair maneuvers regardless of the models and placements of the mobile devices.<\/jats:p>","DOI":"10.3390\/s21248275","type":"journal-article","created":{"date-parts":[[2021,12,13]],"date-time":"2021-12-13T01:29:33Z","timestamp":1639358973000},"page":"8275","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Novel Mobile Device-Based Approach to Quantitative Mobility Measurements for Power Wheelchair Users"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0601-7914","authenticated-orcid":false,"given":"Jicheng","family":"Fu","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Central Oklahoma, Edmond, OK 73034, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuai","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Central Oklahoma, Edmond, OK 73034, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6567-9144","authenticated-orcid":false,"given":"Hongwu","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Science, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan Daniel","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gang","family":"Qian","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Central Oklahoma, Edmond, OK 73034, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MCS.2005.1411382","article-title":"Electric powered wheelchairs","volume":"25","author":"Ding","year":"2005","journal-title":"IEEE Control Syst. 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