Open AccessMiniaturized wireless, skin-integrated sensor networks for quantifying full-body movement behaviors and vital signs in infants
Author(s) -
Hyoyoung Jeong,
Sung Soo Kwak,
Seokwoo Sohn,
Jong Yoon Lee,
Young Joong Lee,
Megan K. O’Brien,
Yoonseok Park,
Raudel Avila,
JinTae Kim,
Jae-Young Yoo,
Masahiro Irie,
Hokyung Jang,
Wei Ouyang,
Nicholas Shawen,
Youn J. Kang,
Seung Sik Kim,
Andreas Tzavelis,
KunHyuck Lee,
Rachel A. Andersen,
Yonggang Huang,
Arun Jayaraman,
Matthew M. Davis,
Thomas P. Shanley,
Lauren S. Wakschlag,
Sheila KroghJespersen,
Shuai Xu,
Shirley W. Ryan,
Richard L. Lieber,
John Rogers
Publication year - 2021
Publication title -
proceedings of the national academy of sciences of the united states of america
Language(s) - English
Resource type - Journals
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.2104925118
Subject(s) - computer science , software deployment , wireless , human–computer interaction , artificial intelligence , telecommunications , operating system
Significance Early detection of infant neuromotor pathologies is critical for timely therapeutic interventions that rely on early-life neuroplasticity. Traditional assessments rely on subjective expert evaluations or specialized medical facilities, making them challenging to scale in remote and/or resource-constrained settings. The results presented here aim to democratize these evaluations using wireless networks of miniaturized, skin-integrated sensors that digitize movement behaviors and vital signs of infants in a cost-effective manner. The resulting data yield full-body motion reconstructions in the form of deidentified infant avatars, along with a range of important cardiopulmonary information. This technology approach enables rapid, routine evaluations of infants at any age via an engineering platform that has potential for use in nearly any setting across developed and developing countries alike.