Assessing motor development with wearables in low-resource settings: feasibility in rural Malawi
Taylor, Elisa; Airaksinen, Manu; Ihamuotila, Rikhard; Kivelä, Milja; Ashorn, Ulla; Haataja, Leena M; Mangani, Charles; Vanhatalo, Sampsa (2025-03-03)
Springer
03.03.2025
Taylor, E., Airaksinen, M., Ihamuotila, R. et al. Assessing motor development with wearables in low-resource settings: feasibility in rural Malawi. Pediatr Res (2025). https://doi.org/10.1038/s41390-025-03818-3
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© The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
https://creativecommons.org/licenses/by/4.0/
© The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202503111948
https://urn.fi/URN:NBN:fi:oulu-202503111948
Tiivistelmä
Abstract
Background:
Tracking of early motor development is essential for all neurodevelopmental assessments. A multisensor wearable system, MAIJU (Motor Assessment of Infants with a JUmpsuit), was recently developed for an objective and scalable measurement of developing motor skills in out-of-hospital settings. Here, we assessed its feasibility in remote low-resource settings.
Methods:
We recruited 44 infants for repeated at-home measurements (total N = 121) with the MAIJU wearable in rural Malawi. We assessed (i) technical quality of the measured wearable data, (ii) reliability of the cloud-based analysis outputs, and (iii) maternal user experience. A dataset from 47 infants (total N = 111 measurements) in Finland served as a reference from a high-resource environment.
Results:
Altogether 94% of the measurements were technically successful. The analysis outputs from the automated cloud pipeline were all comparable to the reference cohort in Finland. The method was rapidly learned by the local study personnel, and it was well received by the mothers.
Conclusion:
Our results suggest that advanced multisensor wearables and cloud-based analytics can be readily used in remote and low-resource settings. Uptake of such objective methods holds promise for harmonizing and increasing equality in developmental assessments, as well as facilitating a wide range of global health studies on early life.
Background:
Tracking of early motor development is essential for all neurodevelopmental assessments. A multisensor wearable system, MAIJU (Motor Assessment of Infants with a JUmpsuit), was recently developed for an objective and scalable measurement of developing motor skills in out-of-hospital settings. Here, we assessed its feasibility in remote low-resource settings.
Methods:
We recruited 44 infants for repeated at-home measurements (total N = 121) with the MAIJU wearable in rural Malawi. We assessed (i) technical quality of the measured wearable data, (ii) reliability of the cloud-based analysis outputs, and (iii) maternal user experience. A dataset from 47 infants (total N = 111 measurements) in Finland served as a reference from a high-resource environment.
Results:
Altogether 94% of the measurements were technically successful. The analysis outputs from the automated cloud pipeline were all comparable to the reference cohort in Finland. The method was rapidly learned by the local study personnel, and it was well received by the mothers.
Conclusion:
Our results suggest that advanced multisensor wearables and cloud-based analytics can be readily used in remote and low-resource settings. Uptake of such objective methods holds promise for harmonizing and increasing equality in developmental assessments, as well as facilitating a wide range of global health studies on early life.
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