{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T02:10:39Z","timestamp":1793239839985,"version":"4.5.0"},"reference-count":20,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T00:00:00Z","timestamp":1785110400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Bioeng. Biotechnol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Postural transitions (PTs) are crucial daily movements often impaired in neurological conditions, impacting autonomy and fall risk. Wearable inertial measurement units (IMUs) enable objective assessment of PTs, but robust algorithms for automatic identification remain limited.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This pilot study used Dynamic Time Warping (DTW), a time-series alignment method that is robust to temporal variations, to automatically identify PTs in healthy subjects (HS) and subjects with Parkinson's Disease (SwPD). For this purpose, 10 participants (5 HS and 5 SwPD) performed 5 postural transition tasks (sit-to-stand, stand-to-sit, supine-to-sit, sit-to-supine, and roll) using a sternum-mounted IMU. Reference PT patterns were generated from previously collected acceleration data representing optimally executed transitions. The DTW algorithm classified each detected candidate transition by minimizing its distance from predefined reference patterns. Classification performance indexes were statistically compared between groups.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Within this pilot dataset, the DTW algorithm correctly identified 118\/118 postural-transition signals in HS and 136\/147 signals in SwPD. Misclassifications in SwPD primarily affected sit-to-stand (31%) and stand-to-sit (19%) transitions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>These preliminary findings support the feasibility of a DTW-based approach for postural-transition identification, although larger independent validation studies are required. Future work should prioritize real-time deployment and larger validation cohorts.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fbioe.2026.1787510","type":"journal-article","created":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T05:41:10Z","timestamp":1785130870000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Automatic identification of postural transitions using a single inertial measurement unit and dynamic time warping: a pilot study in healthy individuals and people with Parkinson\u2019s disease"],"prefix":"10.3389","volume":"14","author":[{"given":"Cinzia","family":"Amici","sequence":"first","affiliation":[{"name":"Department of Mechanical and Industrial Engineering, University of Brescia","place":["Brescia, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roberto","family":"Bussola","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Industrial Engineering, University of Brescia","place":["Brescia, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joel","family":"Pollet","sequence":"additional","affiliation":[{"name":"Department of Clinical and Experimental Sciences, University of Brescia","place":["Brescia, Italy"]},{"name":"IRCCS Fondazione Don Carlo Gnocchi","place":["Milan, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Massimiliano","family":"Gobbo","sequence":"additional","affiliation":[{"name":"Department of Clinical and Experimental Sciences, University of Brescia","place":["Brescia, Italy"]},{"name":"IRCCS Fondazione Don Carlo Gnocchi","place":["Milan, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Riccardo","family":"Buraschi","sequence":"additional","affiliation":[{"name":"IRCCS Fondazione Don Carlo Gnocchi","place":["Milan, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,27]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"6618","DOI":"10.3390\/s20226618","article-title":"Assessment of sit-to-stand transfers during daily life using an accelerometer on the lower back","volume":"20","author":"Adamowicz","year":"2020","journal-title":"Sensors (Basel)"},{"key":"B2","doi-asserted-by":"publisher","first-page":"7011","DOI":"10.3390\/app14167011","article-title":"Kinematic IMU-based assessment of postural transitions: a preliminary application in clinical context","volume":"14","author":"Amici","year":"2024","journal-title":"Appl. Sci. Switz."},{"key":"B3","doi-asserted-by":"publisher","first-page":"1312","DOI":"10.1002\/pmrj.12137","article-title":"Instrumented version of the modified dynamic gait index in patients with neurologic disorders","volume":"11","author":"Anastasi","year":"2019","journal-title":"PM R."},{"key":"B4","doi-asserted-by":"publisher","first-page":"5143","DOI":"10.3390\/s21155143","article-title":"Remote patient monitoring with wearable sensors following knee arthroplasty","volume":"21","author":"Bolam","year":"2021","journal-title":"Sensors."},{"key":"B5","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/j.gaitpost.2022.05.027","article-title":"Temporal and kinematic analyses of timed up and go test in chronic low back pain patients","volume":"96","author":"Buraschi","year":"2022","journal-title":"Gait Posture"},{"key":"B6","doi-asserted-by":"publisher","first-page":"e0155012","DOI":"10.1371\/journal.pone.0155012","article-title":"Anticipatory and compensatory postural adjustments in response to external lateral shoulder perturbations in subjects with parkinson\u2019s disease","volume":"11","author":"de Azevedo","year":"2016","journal-title":"PLoS One"},{"key":"B7","doi-asserted-by":"publisher","first-page":"1542","DOI":"10.14778\/1454159.1454226","article-title":"Querying and mining of time series data: experimental comparison of representations and distance measures","volume":"1","author":"Ding","year":"2008","journal-title":"Proc. VLDB Endow."},{"key":"B8","doi-asserted-by":"publisher","first-page":"975","DOI":"10.1002\/mds.30133","article-title":"Motor symptom variability in parkinson\u2019s disease: implications for personalized trial outcomes?","volume":"40","author":"Janssen Daalen","year":"2025","journal-title":"Mov. Disord."},{"key":"B9","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1145\/2448096.2448103","article-title":"Impact of sensor misplacement on dynamic time warping based human activity recognition using wearable computers","volume":"2012","author":"Kale","year":"2012","journal-title":"Proc. Wirel. Health"},{"key":"B10","doi-asserted-by":"publisher","first-page":"4117","DOI":"10.1038\/s41598-024-54583-y","article-title":"Older adults and individuals with Parkinson\u2019s disease control posture along suborthogonal directions that deviate from the traditional anteroposterior and mediolateral directions","volume":"14","author":"Mangalam","year":"2024","journal-title":"Sci. Rep."},{"key":"B11","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1007\/s10462-025-11275-x","article-title":"A systematic literature review on human activity recognition using smart devices: advances, challenges, and future directions","volume":"11","author":"Qureshi","year":"2025","journal-title":"Artif. Intell. Rev."},{"key":"B12","volume-title":"R: A Language and Environment for Statistical Computing","year":"2024"},{"key":"B13","doi-asserted-by":"publisher","first-page":"1927","DOI":"10.1007\/s00415-019-09348-3","article-title":"Does the MDS-UPDRS provide the precision to assess progression in early Parkinson\u2019s disease? Learnings from the Parkinson\u2019s progression marker initiative cohort","volume":"266","author":"Regnault","year":"2019","journal-title":"J. Neurol."},{"key":"B14","unstructured":"A wearable inertial measurement unit for long-term monitoring in the dependency care area\n          \n          \n            \n              Rodr\u00edguez-Mart\u00edn\n              D.\n            \n            \n              P\u00e9rez-L\u00f3pez\n              C.\n            \n            \n              Sam\u00e0\n              A.\n            \n            \n              Cabestany\n              J.\n            \n            \n              Catal\u00e0\n              A.\n            \n          \n          \n          2013"},{"key":"B15","doi-asserted-by":"publisher","first-page":"2601","DOI":"10.3390\/s21082601","article-title":"Template-based recognition of human locomotion in IMU sensor data using dynamic time warping","volume":"21","author":"Sczuka","year":"2021","journal-title":"Sensors (Basel)"},{"key":"B16","doi-asserted-by":"publisher","first-page":"e60521","DOI":"10.2196\/60521","article-title":"The use of artificial intelligence and wearable inertial measurement units in medicine: systematic review","volume":"13","author":"Smits Serena","year":"2025","journal-title":"JMIR Mhealth Uhealth"},{"key":"B17","doi-asserted-by":"publisher","first-page":"733","DOI":"10.1097\/01.phm.0000179521.70639.83","article-title":"International classification of functioning, disability, and health (ICF): a promising framework and classification for rehabilitation medicine","volume":"84","author":"Stucki","year":"2005","journal-title":"Am. J. Phys. Med. Rehabil."},{"key":"B18","doi-asserted-by":"crossref","DOI":"10.1109\/MeMeA.2016.7533745","volume-title":"Monitoring of Gait Performance Using Dynamic Time Warping on IMU-Sensor Data","author":"Wang","year":"2016"},{"key":"B19","doi-asserted-by":"publisher","first-page":"2237","DOI":"10.3390\/s19102237","article-title":"Imu consensus exception detection with dynamic time warping\u2014a comparative approach","volume":"19","author":"Yang","year":"2019","journal-title":"Sensors"},{"key":"B20","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1186\/1743-0003-9-75","article-title":"Sit-stand and stand-sit transitions in older adults and patients with Parkinson\u2019s disease: event detection based on motion sensors versus force plates","volume":"9","author":"Zijlstra","year":"2012","journal-title":"J. Neuroeng Rehabil."}],"container-title":["Frontiers in Bioengineering and Biotechnology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fbioe.2026.1787510\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T05:41:11Z","timestamp":1785130871000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fbioe.2026.1787510\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,27]]},"references-count":20,"alternative-id":["10.3389\/fbioe.2026.1787510"],"URL":"https:\/\/doi.org\/10.3389\/fbioe.2026.1787510","relation":{},"ISSN":["2296-4185"],"issn-type":[{"value":"2296-4185","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,27]]},"article-number":"1787510"}}