Identification of diseases based on the use of inertial sensors: a systematic review

article

Ponciano, Vasco
Pires, Ivan
Ribeiro, Fernando Reinaldo
Marques, Gonçalo
Villasana, Maria
Garcia, Nuno
Zdravevski, Eftim
Spinsante, Susanna

Multidisciplinary Digital Publishing Institute

PONCIANO, V. [et al.] (2020) - Identification of diseases based on the use of inertial sensors: a systematic review. Electronics. ISSN 2079-9292. Vol 9, nº 5, p. 1-17. Doi: 10.3390/electronics9050778

2079-9292

10.3390/electronics9050778

Identification of diseases based on the use of inertial sensors: a systematic review

Wearable electronic devices
Diseases
Monitoring
Automatic identification

UIDB/EEA/50008/2020

2020-05-12T11:42:44Z
2020-05-12T11:42:44Z
2020-05

Inertial sensors are commonly embedded in several devices, including smartphones, and other specific devices. This type of sensors may be used for different purposes, including the recognition of different diseases. Several studies are focused on the use of accelerometer for the automatic recognition of different diseases, and it may powerful the different treatments with the use of less invasive and painful techniques for patients. This paper is focused in the systematic review of the studies available in the literature for the automatic recognition of different diseases with accelerometer sensors. The disease that is the most reliably detectable disease using accelerometer sensors, available in 54% of the analyzed studies, is the Parkinson’s disease. The machine learning methods implements for the recognition of Parkinson’s disease reported an accuracy of 94%. Other diseases are recognized in less number that will be subject of further analysis in the future.
info:eu-repo/semantics/publishedVersion

openAccess
http://creativecommons.org/licenses/by/4.0/

eng