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Each sensor modality is validated against data from gold-standard equipment using established algorithms and laboratory tasks. Interbeat interval (IBI) data obtained from the LittleBeats\u2122 ECG sensor indicate acceptable mean absolute percent error rates for both adults (Study 1, N = 16) and infants (Study 2, N = 5) across low- and high-challenge sessions and expected patterns of change in respiratory sinus arrythmia (RSA). For automated activity recognition (upright vs. walk vs. glide vs. squat) using accelerometer data from the LittleBeats\u2122 IMU (Study 3, N = 12 adults), performance was good to excellent, with smartphone (industry standard) data outperforming LittleBeats\u2122 by less than 4 percentage points. Speech emotion recognition (Study 4, N = 8 adults) applied to LittleBeats\u2122 versus smartphone audio data indicated a comparable performance, with no significant difference in error rates. On an automatic speech recognition task (Study 5, N = 12 adults), the best performing algorithm yielded relatively low word error rates, although LittleBeats\u2122 (4.16%) versus smartphone (2.73%) error rates were somewhat higher. Together, these validation studies indicate that LittleBeats\u2122 sensors yield a data quality that is largely comparable to those obtained from gold-standard devices and established protocols used in prior research.<\/jats:p>","DOI":"10.3390\/s24030901","type":"journal-article","created":{"date-parts":[[2024,1,30]],"date-time":"2024-01-30T12:06:58Z","timestamp":1706616418000},"page":"901","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Preliminary Technical Validation of LittleBeats\u2122: A Multimodal Sensing Platform to Capture Cardiac Physiology, Motion, and Vocalizations"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1917-054X","authenticated-orcid":false,"given":"Bashima","family":"Islam","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nancy L.","family":"McElwain","sequence":"additional","affiliation":[{"name":"Department of Human Development and Family Studies, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA"},{"name":"Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0092-8071","authenticated-orcid":false,"given":"Jialu","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria I.","family":"Davila","sequence":"additional","affiliation":[{"name":"Research Triangle Institute, Research Triangle Park, NC 27709, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yannan","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Human Development and Family Studies, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kexin","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Human Development and Family Studies, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jordan M.","family":"Bodway","sequence":"additional","affiliation":[{"name":"Department of Human Development and Family Studies, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ashutosh","family":"Dhekne","sequence":"additional","affiliation":[{"name":"School of Computer Science, Georgia Institute of Technology, Atlanta, GA 30332, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Romit","family":"Roy Choudhury","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5631-2893","authenticated-orcid":false,"given":"Mark","family":"Hasegawa-Johnson","sequence":"additional","affiliation":[{"name":"Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA"},{"name":"Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1146\/annurev-clinpsy-032816-044949","article-title":"Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning","volume":"13","author":"Mohr","year":"2017","journal-title":"Annu. 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