{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T19:00:09Z","timestamp":1787166009004,"version":"build-2736575974"},"posted":{"date-parts":[[2024,11,21]]},"group-title":"Neurology","reference-count":30,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T00:00:00Z","timestamp":1732147200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/publicdomain\/zero\/1.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2024,11,21]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>\n                  The COVID-19 pandemic and increased demands for neurologists have inspired the creation of remote, digitalized tests of neurological functions. This study investigates two tests from the Neurological Functional Tests Suite (NeuFun-TS) smartphone application, the \u201cPostural Sway\u201d and \u201cPronator Drift\u201d tests. These tests capture different domains of postural control and motoric dysfunction in healthy volunteers (n=13) and people with neurological disorders (n=68 relapsing-remitting multiple sclerosis [MS]; n=21 secondary progressive MS; n=23 primary progressive MS; n=13 other inflammatory neurological diseases; n=21 non-inflammatory neurological diseases; n=4 clinically isolated syndrome; n=1 radiologically isolated syndrome). Smartphone accelerometer data was transformed into digital biomarkers, which were filtered in the training cohort (\u223c80% of subjects) for test-retest reproducibility and correlations with subdomains of neurological examinations and validated imaging biomarkers. The independent validation cohort (\u223c20%) determined whether biomarker models outperformed the best single digital biomarkers. Postural sway acceleration magnitude in the eyes closed and feet together stance demonstrated the highest reliability (ICC=.706), strongest correlations with age (Pearson r&lt;=.82) and clinical and imaging outcomes (r&lt;=.65, p&lt;0.001) and stronger predictive value for sway-relevant neurological disability outcomes than models that aggregated multiple biomarkers (coefficient of determination R\n                  <jats:sup>2<\/jats:sup>\n                  =.46 vs .38). The pronator drift test only captured cerebellar dysfunction, had less reproducible biomarkers, but provided additive value when combined with postural sway biomarkers into models predicting global scales of neurological disability. In conclusion, a simple 1-minute postural sway test accurately measures body oscillations that increase with natural aging and differentiates them from abnormally increased body oscillations in people with neurological disabilities.\n                <\/jats:p>","DOI":"10.1101\/2024.11.20.24317196","type":"posted-content","created":{"date-parts":[[2024,11,21]],"date-time":"2024-11-21T16:15:16Z","timestamp":1732205716000},"source":"Crossref","is-referenced-by-count":1,"title":["Smartphone Postural Sway and Pronator Drift tests as Measures of Neurological Disability"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-5624-3232","authenticated-orcid":false,"given":"Michael","family":"Calcagni","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1392-0629","authenticated-orcid":false,"given":"Peter","family":"Kosa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0959-9430","authenticated-orcid":false,"given":"Bibi","family":"Bielekova","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2024112507202979000_2024.11.20.24317196v1.1","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.gaitpost.2018.10.005","article-title":"Sosnoff JJ: Smartphone technology can measure postural stability and discriminate fall risk in older adults","volume":"67","year":"2019","journal-title":"Gait & posture"},{"issue":"1","key":"2024112507202979000_2024.11.20.24317196v1.2","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1038\/s41598-023-49299-4","article-title":"Giovannoni G: Use of smartphone-based remote assessments of multiple sclerosis in Floodlight Open, a global, prospective, open-access study","volume":"14","year":"2024","journal-title":"Scientific Reports"},{"issue":"1","key":"2024112507202979000_2024.11.20.24317196v1.3","first-page":"e12243","article-title":"Unsupervised mobile cognitive testing for use in preclinical Alzheimer\u2019s disease","volume":"13","year":"2021","journal-title":"Alzheimer\u2019s & Dementia: Diagnosis, Assessment & Disease Monitoring"},{"issue":"4","key":"2024112507202979000_2024.11.20.24317196v1.4","doi-asserted-by":"crossref","first-page":"e244266","DOI":"10.1001\/jamanetworkopen.2024.4266","article-title":"Manoochehri M: Reliability and Validity of Smartphone Cognitive Testing for Frontotemporal Lobar Degeneration","volume":"7","year":"2024","journal-title":"JAMA Network Open"},{"key":"2024112507202979000_2024.11.20.24317196v1.5","first-page":"283","article-title":"Ritchie C: Self-administered cognitive testing by older adults at-risk for cognitive decline","volume":"7","year":"2020","journal-title":"The journal of prevention of Alzheimer\u2019s disease"},{"key":"2024112507202979000_2024.11.20.24317196v1.6","doi-asserted-by":"crossref","unstructured":"Boukhvalova AK , Fan O , Weideman AM , Harris T , Kowalczyk E , Pham L , Kosa P , Bielekova B: Smartphone level test measures disability in several neurological domains for patients with multiple sclerosis. 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