Wearables for Movement Analysis in Healthcare

Paolo Capodaglio^{1

2}, Veronica Cimolin³

Affiliations

¹ Orthopaedic Rehabilitation Unit and Research Lab for Biomechanics, Rehabilitation and Ergonomics, Ospedale San Giuseppe, Istituto Auxologico Italiano, IRCCS, via Cadorna 90, 28824 Piancavallo di Oggebbio, Italy.
² Department Surgical Sciences, Physical and Rehabilitation Medicine, University of Torino, 10126 Torino, Italy.
³ Department of Electronics, Information and Bioengineering, Politecnico di Milan, Piazza Leonardo da Vinci 32, 20133 Milan, Italy.

PMID: 35632128
PMCID: PMC9145753
DOI: 10.3390/s22103720

Editorial

Wearables for Movement Analysis in Healthcare

Paolo Capodaglio et al. Sensors (Basel). 2022.

. 2022 May 13;22(10):3720.

doi: 10.3390/s22103720.

Authors

Paolo Capodaglio^{1

2}, Veronica Cimolin³

Affiliations

¹ Orthopaedic Rehabilitation Unit and Research Lab for Biomechanics, Rehabilitation and Ergonomics, Ospedale San Giuseppe, Istituto Auxologico Italiano, IRCCS, via Cadorna 90, 28824 Piancavallo di Oggebbio, Italy.
² Department Surgical Sciences, Physical and Rehabilitation Medicine, University of Torino, 10126 Torino, Italy.
³ Department of Electronics, Information and Bioengineering, Politecnico di Milan, Piazza Leonardo da Vinci 32, 20133 Milan, Italy.

PMID: 35632128
PMCID: PMC9145753
DOI: 10.3390/s22103720

Abstract

Quantitative movement analysis is widely used in clinical practice and research to objectively and thoroughly investigate movement disorder [...].

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Conflict of interest statement

The authors declare no conflict of interest.

Cited by

Context Recognition Algorithms for Energy-Efficient Freezing-of-Gait Detection in Parkinson's Disease.
Borzì L, Sigcha L, Olmo G. Borzì L, et al. Sensors (Basel). 2023 Apr 30;23(9):4426. doi: 10.3390/s23094426. Sensors (Basel). 2023. PMID: 37177629 Free PMC article.

References

1. Zago M., Tarabini M., Delfino Spiga M., Ferrario C., Bertozzi F., Sforza C., Galli M. Machine-Learning Based Determination of Gait Events from Foot-Mounted Inertial Units. Sensors. 2021;21:839. doi: 10.3390/s21030839. - DOI - PMC - PubMed
1. Lueken M., Mueller L., Decker M.G., Bollheimer C., Leonhardt S., Ngo C. Evaluation and Application of a Customizable Wireless Platform: A Body Sensor Network for Unobtrusive Gait Analysis in Everyday Life. Sensors. 2020;20:7325. doi: 10.3390/s20247325. - DOI - PMC - PubMed
1. Amitrano F., Coccia A., Ricciardi C., Donisi L., Cesarelli G., Capodaglio E.M., D’Addio G. Design and Validation of an E-Textile-Based Wearable Sock for Remote Gait and Postural Assessment. Sensors. 2020;20:6691. doi: 10.3390/s20226691. - DOI - PMC - PubMed
1. Cimolin V., Vismara L., Ferraris C., Amprimo G., Pettiti G., Lopez R., Galli M., Cremascoli R., Sinagra S., Mauro A., et al. Computation of Gait Parameters in Post Stroke and Parkinson’s Disease: A Comparative Study Using RGB-D Sensors and Optoelectronic Systems. Sensors. 2022;22:824. doi: 10.3390/s22030824. - DOI - PMC - PubMed
1. Schifino G., Cimolin V., Pau M., da Cunha M.J., Leban B., Porta M., Galli M., Souza Pagnussat A. Functional Electrical Stimulation for Foot Drop in Post-Stroke People: Quantitative Effects on Step-to-Step Symmetry of Gait Using a Wearable Inertial Sensor. Sensors. 2021;21:921. doi: 10.3390/s21030921. - DOI - PMC - PubMed

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Wearables for Movement Analysis in Healthcare

Affiliations

Wearables for Movement Analysis in Healthcare

Authors

Affiliations

Abstract

Conflict of interest statement

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References

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LinkOut - more resources

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