{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T17:26:31Z","timestamp":1775064391176,"version":"3.50.1"},"reference-count":25,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,3,29]],"date-time":"2018-03-29T00:00:00Z","timestamp":1522281600000},"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>Wearable biosensors, such as those embedded in smart phones, can provide data to assess neuro-motor control in mobile settings, at homes, schools, workplaces and clinics. However, because most machine learning algorithms currently used to analyze such data require several steps that depend on human heuristics, the analyses become computationally expensive and rather subjective. Further, there is no standardized scale or set of tasks amenable to take advantage of such technology in ways that permit broad dissemination and reproducibility of results. Indeed, there is a critical need for fully objective automated analytical methods that easily handle the deluge of data these sensors output, while providing standardized scales amenable to apply across large sections of the population, to help promote personalized-mobile medicine. Here we use an open-access data set from Kaggle.com to illustrate the use of a new statistical platform and standardized data types applied to smart phone accelerometer and gyroscope data from 30 participants, performing six different activities. We report full distinction without confusion of the activities from the Kaggle set using a single parameter (linear acceleration or angular speed). We further extend the use of our platform to characterize data from commercially available smart shoes, using gait patterns within a set of experiments that probe nervous systems functioning and levels of motor control.<\/jats:p>","DOI":"10.3390\/s18041025","type":"journal-article","created":{"date-parts":[[2018,3,29]],"date-time":"2018-03-29T12:51:56Z","timestamp":1522327916000},"page":"1025","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Statistical Platform for Individualized Behavioral Analyses Using Biophysical Micro-Movement Spikes"],"prefix":"10.3390","volume":"18","author":[{"given":"Elizabeth","family":"Torres","sequence":"first","affiliation":[{"name":"Psychology Department, Rutgers University, Piscataway, NJ 08854, USA"},{"name":"Computer Science Department, Computational Biomedicine Imaging and Modeling, Rutgers Center for Cognitive Science, Rutgers University, Piscataway, NJ 08854, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6049-9817","authenticated-orcid":false,"given":"Joe","family":"Vero","sequence":"additional","affiliation":[{"name":"Bioengineering Department, Rutgers University, Piscataway, NJ 08854, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richa","family":"Rai","sequence":"additional","affiliation":[{"name":"Psychology Department, Rutgers University, Piscataway, NJ 08854, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,3,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"300ps317","DOI":"10.1126\/scitranslmed.aaa9970","article-title":"Precision medicine: Beyond the inflection point","volume":"7","author":"Hawgood","year":"2015","journal-title":"Sci. Transl. Med."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1176\/appi.ajp.2014.14020138","article-title":"The NIMH Research Domain Criteria (RDoC) Project: Precision medicine for psychiatry","volume":"171","author":"Insel","year":"2014","journal-title":"Am. J. Psychiatry"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"8","DOI":"10.3389\/fneur.2016.00008","article-title":"Toward Precision Psychiatry: Statistical Platform for the Personalized Characterization of Natural Behaviors","volume":"7","author":"Torres","year":"2016","journal-title":"Front. Neurol."},{"key":"ref_4","unstructured":"Torres, E.B. (2018). Objective Biometric Methods for the Diagnosis and Treatment of Nervous System Disorders, Elsevier Science."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1007\/s00221-011-2892-8","article-title":"Two classes of movements in motor control","volume":"215","author":"Torres","year":"2011","journal-title":"Exp. Brain Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fped.2016.00121","article-title":"Neonatal Diagnostics: Toward Dynamic Growth Charts of Neuromotor Control","volume":"4","author":"Torres","year":"2016","journal-title":"Front. Pediatr."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"32","DOI":"10.3389\/fnint.2013.00032","article-title":"Autism: The micro-movement perspective","volume":"7","author":"Torres","year":"2013","journal-title":"Front. Integr. Neurosci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"748","DOI":"10.1176\/appi.ajp.2010.09091379","article-title":"Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders","volume":"167","author":"Insel","year":"2010","journal-title":"Am. J. Psychiatry"},{"key":"ref_9","unstructured":"Anguita, D., Ghio, A., Oneto, L., Parra, X., and Reyes-Ortiz, J.L. (2013, January 24\u201326). 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Biol."},{"key":"ref_15","unstructured":"Kalampratsidou, V., Mistry, S., Kolevzon, A., and Torres, E.B. (2017, January 11\u201315). Personalized characterization of longitudinal changes towards typical signatures of gait control in SHANK3 IGF-1 clinical trial. Proceedings of the Annual Meeting of the Society for Neuroscience, Washington, DC, USA."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"22","DOI":"10.3389\/fnint.2016.00022","article-title":"Characterization of the Statistical Signatures of Micro-Movements Underlying Natural Gait Patterns in Children with Phelan McDermid Syndrome: Towards Precision-Phenotyping of Behavior in ASD","volume":"10","author":"Torres","year":"2016","journal-title":"Front. Integr. Neurosci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Lazcko, J., and Latash, M. (2016). Rethinking the Study of Volition for Clinical Use. Progress in Motor Control: Theories and Translations, Springer.","DOI":"10.1007\/978-3-319-47313-0"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"46","DOI":"10.3389\/fnint.2013.00046","article-title":"Give spontaneity and self-discovery a chance in ASD: Spontaneous peripheral limb variability as a proxy to evoke centrally driven intentional acts","volume":"7","author":"Torres","year":"2013","journal-title":"Front. Integr. Neurosci."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Torres, E.B., and Whyatt, C.P. (2017). Why Study Movement Variability in Autism?. Autism: The Movement Sensing Approach, CRC Press-Taylor and Francis.","DOI":"10.1201\/9781315372518"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"50","DOI":"10.3389\/fnint.2013.00050","article-title":"The rates of change of the stochastic trajectories of acceleration variability are a good predictor of normal aging and of the stage of Parkinson\u2019s disease","volume":"7","author":"Torres","year":"2013","journal-title":"Front. Integr. Neurosci."},{"key":"ref_21","unstructured":"Kalampratsidou, V., and Torres, E.B. (2018, January 28\u201330). Dancing to one\u2019s heartbeat: A study of physiological signal entrainment through the real-time sonification of heart rate data. Proceedings of the Movement and Computing (MOCO\u201918), Genoa, Italy."},{"key":"ref_22","unstructured":"Kalampratsidou, V., and Torres, E.B. (2018, January 28\u201330). Extracting sensory and contextual information from the motor stream. 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Neurosci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"37422","DOI":"10.1038\/srep37422","article-title":"Motor noise is rich signal in autism research and pharmacological treatments","volume":"6","author":"Torres","year":"2016","journal-title":"Sci. Rep."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/4\/1025\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:58:57Z","timestamp":1760194737000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/4\/1025"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,3,29]]},"references-count":25,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2018,4]]}},"alternative-id":["s18041025"],"URL":"https:\/\/doi.org\/10.3390\/s18041025","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,3,29]]}}}