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Di J, Tuttle PG, Adamowicz L, Lin W, Zhang H, Psaltos D, Selig J, Bai J, Karahanoglu FI, Sheriff P, Seelam V, Williams B, Ghafoor S, Demanuele C, Santamaria M, Cai X. Monitoring Activity and Gait in Children (MAGIC) using digital health technologies. Pediatr Res 2024:10.1038/s41390-024-03147-x. [PMID: 38514860 DOI: 10.1038/s41390-024-03147-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 02/22/2024] [Accepted: 03/02/2024] [Indexed: 03/23/2024]
Abstract
BACKGROUND Digital health technologies (DHTs) can collect gait and physical activity in adults, but limited studies have validated these in children. This study compared gait and physical activity metrics collected using DHTs to those collected by reference comparators during in-clinic sessions, to collect a normative accelerometry dataset, and to evaluate participants' comfort and their compliance in wearing the DHTs at-home. METHODS The MAGIC (Monitoring Activity and Gait in Children) study was an analytical validation study which enrolled 40, generally healthy participants aged 3-17 years. Gait and physical activity were collected using DHTs in a clinical setting and continuously at-home. RESULTS Overall good to excellent agreement was observed between gait metrics extracted with a gait algorithm from a lumbar-worn DHT compared to ground truth reference systems. Majority of participants either "agreed" or "strongly agreed" that wrist and lumbar DHTs were comfortable to wear at home, respectively, with 86% (wrist-worn DHT) and 68% (lumbar-worn DHT) wear-time compliance. Significant differences across age groups were observed in multiple gait and activity metrics obtained at home. CONCLUSIONS Our findings suggest that gait and physical activity data can be collected from DHTs in pediatric populations with high reliability and wear compliance, in-clinic and in home environments. TRIAL REGISTRATION ClinicalTrials.gov: NCT04823650 IMPACT: Digital health technologies (DHTs) have been used to collect gait and physical activity in adult populations, but limited studies have validated these metrics in children. The MAGIC study comprehensively validates the performance and feasibility of DHT-measured gait and physical activity in the pediatric population. Our findings suggest that reliable gait and physical activity data can be collected from DHTs in pediatric populations, with both high accuracy and wear compliance both in-clinic and in home environments. The identified across-age-group differences in gait and activity measurements highlighted their potential clinical value.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Xuemei Cai
- Pfizer, Inc., Cambridge, MA, USA
- Tufts Medical Center, Boston, MA, USA
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Airaksinen M, Vaaras E, Haataja L, Räsänen O, Vanhatalo S. Automatic assessment of infant carrying and holding using at-home wearable recordings. Sci Rep 2024; 14:4852. [PMID: 38418850 PMCID: PMC10901884 DOI: 10.1038/s41598-024-54536-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 02/14/2024] [Indexed: 03/02/2024] Open
Abstract
Assessing infant carrying and holding (C/H), or physical infant-caregiver interaction, is important for a wide range of contexts in development research. An automated detection and quantification of infant C/H is particularly needed in long term at-home studies where development of infants' neurobehavior is measured using wearable devices. Here, we first developed a phenomenological categorization for physical infant-caregiver interactions to support five different definitions of C/H behaviors. Then, we trained and assessed deep learning-based classifiers for their automatic detection from multi-sensor wearable recordings that were originally used for mobile assessment of infants' motor development. Our results show that an automated C/H detection is feasible at few-second temporal accuracy. With the best C/H definition, the automated detector shows 96% accuracy and 0.56 kappa, which is slightly less than the video-based inter-rater agreement between trained human experts (98% accuracy, 0.77 kappa). The classifier performance varies with C/H definition reflecting the extent to which infants' movements are present in each C/H variant. A systematic benchmarking experiment shows that the widely used actigraphy-based method ignores the normally occurring C/H behaviors. Finally, we show proof-of-concept for the utility of the novel classifier in studying C/H behavior across infant development. Particularly, we show that matching the C/H detections to individuals' gross motor ability discloses novel insights to infant-parent interaction.
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Affiliation(s)
- Manu Airaksinen
- BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, New Children's Hospital and HUS Imaging, Helsinki University Hospital, Helsinki, Finland.
- Department of Physiology, University of Helsinki, Biomedicum 1, Room B129b, Haartmaninkatu 8, 00290, Helsinki, Finland.
| | - Einari Vaaras
- Unit of Computing Sciences, Tampere University, P.O. Box 553, 33101, Tampere, Finland
| | - Leena Haataja
- BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, New Children's Hospital and HUS Imaging, Helsinki University Hospital, Helsinki, Finland
- Department of Pediatric Neurology, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Okko Räsänen
- Unit of Computing Sciences, Tampere University, P.O. Box 553, 33101, Tampere, Finland
| | - Sampsa Vanhatalo
- BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, New Children's Hospital and HUS Imaging, Helsinki University Hospital, Helsinki, Finland
- Department of Physiology, University of Helsinki, Biomedicum 1, Room B129b, Haartmaninkatu 8, 00290, Helsinki, Finland
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McElwain NL, Fisher MC, Nebeker C, Bodway JM, Islam B, Hasegawa-Johnson M. Evaluating Users' Experiences of a Child Multimodal Wearable Device: Mixed Methods Approach. JMIR Hum Factors 2024; 11:e49316. [PMID: 38329785 PMCID: PMC10884896 DOI: 10.2196/49316] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 09/26/2023] [Accepted: 09/29/2023] [Indexed: 02/09/2024] Open
Abstract
BACKGROUND Wearable devices permit the continuous, unobtrusive collection of data from children in their natural environments and can transform our understanding of child development. Although the use of wearable devices has begun to emerge in research involving children, few studies have considered families' experiences and perspectives of participating in research of this kind. OBJECTIVE Through a mixed methods approach, we assessed parents' and children's experiences of using a new wearable device in the home environment. The wearable device was designed specifically for use with infants and young children, and it integrates audio, electrocardiogram, and motion sensors. METHODS In study 1, semistructured phone interviews were conducted with 42 parents of children aged 1 month to 9.5 years who completed 2 day-long recordings using the device, which the children wore on a specially designed shirt. In study 2, a total of 110 parents of children aged 2 months to 5.5 years responded to a questionnaire assessing their experience of completing 3 day-long device recordings in the home. Guided by the Digital Health Checklist, we assessed parental responses from both studies in relation to the following three key domains: (1) access and usability, (2) privacy, and (3) risks and benefits. RESULTS In study 1, most parents viewed the device as easy to use and safe and remote visits as convenient. Parents' views on privacy related to the audio recordings were more varied. The use of machine learning algorithms (vs human annotators) in the analysis of the audio data, the ability to stop recordings at any time, and the view that the recordings reflected ordinary family life were some reasons cited by parents who expressed minimal, if any, privacy concerns. Varied risks and benefits were also reported, including perceived child comfort or discomfort, the need to adjust routines to accommodate the study, the understanding gained from the study procedures, and the parent's and child's enjoyment of study participation. In study 2, parents' ratings on 5 close-ended items yielded a similar pattern of findings. Compared with a "neutral" rating, parents were significantly more likely to agree that (1) device instructions were helpful and clear (t109=-45.98; P<.001), (2) they felt comfortable putting the device on their child (t109=-22.22; P<.001), and (3) they felt their child was safe while wearing the device (t109=-34.48; P<.001). They were also less likely to worry about the audio recordings gathered by the device (t108=6.14; P<.001), whereas parents' rating of the burden of the study procedures did not differ significantly from a "neutral" rating (t109=-0.16; P=.87). CONCLUSIONS On the basis of parents' feedback, several concrete changes can be implemented to improve this new wearable platform and, ultimately, parents' and children's experiences of using child wearable devices in the home setting.
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Affiliation(s)
- Nancy L McElwain
- Department of Human Development and Family Studies, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Beckman Institute for Advanced Science & Technology, University of Illinois Urbana-Champaign, Urbana, IL, United States
| | - Meghan C Fisher
- Department of Human Development and Family Studies, University of Illinois Urbana-Champaign, Urbana, IL, United States
| | - Camille Nebeker
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, United States
| | - Jordan M Bodway
- Department of Human Development and Family Studies, University of Illinois Urbana-Champaign, Urbana, IL, United States
| | - Bashima Islam
- Department of Electrical and Computer Engineering, Worcester Polytechnic Institute, Worcester, MA, United States
| | - Mark Hasegawa-Johnson
- Beckman Institute for Advanced Science & Technology, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, United States
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The comfort of adolescent patients and their parents with mobile sensing and digital phenotyping. COMPUTERS IN HUMAN BEHAVIOR 2023. [DOI: 10.1016/j.chb.2022.107603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Gautheron L, Rochat N, Cristia A. Managing, storing, and sharing long-form recordings and their annotations. LANG RESOUR EVAL 2022. [DOI: 10.1007/s10579-022-09579-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Reeb-Sutherland B, Williams LR, Gartstein MA, Fox NA. Methodological advances in the characterization and understanding of caregiver-infant interactions. Infant Behav Dev 2021; 66:101668. [PMID: 34814006 DOI: 10.1016/j.infbeh.2021.101668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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