Frailty syndrome is becoming a major challenge of the aging population. The prevalence of frailty is 17%, whereas pre-frailty may affect up to 60% of individuals ? 65 years. Due to reduced physiological reserve, frail individuals are susceptible to chronic and acute heart diseases, as well as to surgical interventions, which are followed by a longer recovery and a higher incidence of complications. Pre-frailty is clinically reversible thus progression to more
advanced stages could be prevented by timely prescription of appropriate exercise training. Unfortunately, the existing methods, which rely on various
indexes and questionnaires, are neither sufficiently sensitive for detecting pre-frailty, nor suitable for monitoring frailty dynamics in the course of exercise
training. A systematic review showed that frail patients usually exhibit an impairment in the function of autonomous nervous system (ANS), resulting in a
decreased capacity to maintain homeostasis when exposed to daily physical stressors (eg, stair climbing, postural transition). We hypothesize that timely
detection of ANS parameter deviation from the norm would facilitate identification of pre-frailty stage, whereas monitoring of parameter dynamics over time would enable remote assessment of the effectiveness of exercise training at home environment. The FrailHeart project aims to develop unobtrusive
wearable technology for long-term monitoring of ANS characterizing parameters and frailty feature dynamics when exposed to daily physical stressors.
Patients with cardiovascular disease and frailty, evaluated relying on a clinical methodology, will be enrolled in a study. Monitoring will start at Kulautuva
Rehabilitation Hospital of LUHS Kaunas Clinics (up to 20 days), and will be continued in outpatient (> 1 month). It is expected that the knowledge gained
from monitoring frailty patients using the developed unobtrusive technology will be valuable for personalizing outpatient exercised training.
Project funding:
Projects funded by the Research Council of Lithuania (RCL), Projects carried out by researchers’ teams
Project results:
Intended project outcomes:
1. Embedded algorithms for monitoring of autonomic nervous system function using unobtrusive low power wearable technology.
2. Algorithms for automatic detection of frailty features and daily physical stressors.
3. A methodological framework for personalized exercise training at home environment using unobtrusive long-term monitoring technology.
Period of project implementation: 2020-06-01 - 2022-04-30
Project coordinator: Kaunas University of Technology
Project partners: Lithuanian University of Health Sciences, Lietuvos sveikatos mokslų universiteto ligoninė Kauno klinikos
