Laura García-Durán, Silvia Claros, Pablo Zamorano-González, Marta González-García, Laura Carrillo-Franco, Marina Ponce-Velasco, Belén Gago, María García-Fernández, Manuel Víctor López-González, Ana Aiastui
Teaching the physiology of the human body in non-formal spaces: pilot experience of a Service-Learning methodology and the interaction between students of different educational levels
Frontiers in physiology
wristworn activity monitors seen widespread adoption recent times particularly young sportoriented cohorts usage among older adults remained relatively low main limitations regards lack medical insights current mainstream activity trackers provide older subjects one important research areas investigation currently possibility extrapolating clinical information wearable devices research question study understanding whether accelerometry data collected 7days freeliving environments using consumerbased wristband device conjunction datadriven machine learning algorithms able predict hand grip strength possible conditions categorized hand grip strength general population consisting middleaged older adults results regression analysis reveal performance developed models notably superior simple meanpredicting dummy regressor improvement absolute terms may appear modest mean absolute error 632 kg males 453 kg females falls within range considered sufficiently accurate grip strength estimation classification models instead excel categorizing individuals frailprefrail healthy depending tscore levels applied frailtyprefrailty definition cutoff values frailty vary results suggest models moderately detect characteristics associated frailty aucroc 070 males 076 females viably detect characteristics associated frailtyprefrailty aucroc 086 males 087 females results study enable adoption wearable devices efficient tool clinical assessment older adults multimorbidities improving advancing integrated care diagnosis early screening number widespread diseases