Cyber-Human Systems for Personalized Well-being and Health

Recruiting

• Conditions: Geriatric Health Services; Health Services for the Elderly

• Registration Number: NCT06490783
• Lead Sponsor: Istituto per la Ricerca e l'Innovazione Biomedica

Brief Summary

The purpose of the present study is to evaluate the effectiveness of using multi-parameter monitoring devices in the elderly to improve their quality of life not already understood as the absence of disease but in a logic that is intrinsically linked to the body-mind relationship, which is increasingly significant as biological age advances. The study will be conducted on a sample of volunteer elderly subjects who will wear devices capable of constantly monitoring vital parameters such as heart rate, physical activity, sleep quality, stress levels and higher level activities, linked sensory and cognitive aspects ecologically integrated with the elderly person's living environment, in the sense of an evaluative and qualitative focus on relationships within the person's area of action/interaction, possibly supported and stimulated by individualized and easily usable activities. The signals interpreted and returned by the technology to the elderly person who uses it can also act as a reassuring self-assessment of even normal body states, sometimes experienced as threatening and anxiogenic, thus stressful. The collection and management of these data may serve as a reference to the recognition of distress signals and complex experiences (e.g., depressive) that normally have significant effects on mental health, understood as intrinsically linked to the health of the body.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2024-06-17
• Study Start: 2024-07-01
• Study First Submitted QC: 2024-07-01
• Study First Posted: 2024-07-08
• Status Verified: 2025-04
• Last Update Submitted: 2025-04-29
• Last Update Posted: 2025-05-01
• Primary Completion: 2025-12-31
• Study Completion: 2026-05-31

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 10

Inclusion Criteria

• healthy male and female aged 60 years and older
• signing of informed consent

Exclusion Criteria

• chronic diseases
• cardiovascular disease
• presence of dementia and/or depression
• presence of confirmed paranoid or psychotic symptoms

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Distance traveled	Through study completion, an average of 1 year	This indicates the actual physical length each subject covered during activity. It's usually measured in miles or kilometers. Distance traveled can be calculated based on the number of steps you take and your stride length (the distance between two consecutive footfalls with the same foot).
Heart Rate(HR)	Through study completion, an average of 1 year	The chest strap Polar H10 uses an electrocardiogram (ECG) sensor to detect the electrical activity of the heart and calculate heart rate in beats per minute (bpm).
Heart rate variability (HRV)	Through study completion, an average of 1 year	The chest strap Polar H10 measures the time intervals between successive heart beats and calculates Heart Rate Variability (HRV) in milliseconds (ms).
Steps taken	Through study completion, an average of 1 year	This refers to the total number of times each subject take a step with either foot. It's a basic unit to measure overall activity level. Fitness trackers typically use steps to monitor movement throughout the day.
Facial emotion recognition	Through study completion, an average of 1 year	The smartphone's camera records facial expressions in order to evaluate and quantify human emotions.; The Artificial Intelligence (AI) algorithms, recognizing the human face, identify important facial features and examine them to categorize different facial emotions. The emotions associated with these facial expressions are then extracted.
Calories burned	Through study completion, an average of 1 year	This refers to the amount of energy each subject's body expends during activity. It's measured in calories (kcal). The number of calories burned depends on various factors like weight, height, activity intensity (e.g., walking vs running), and duration. Fitness trackers typically estimate calorie burn based on steps taken, distance traveled, and personal information.

Trial Locations

Locations (1)

Institute for Biomedical Research and Innovation (IRIB)-National Reasearch Council (CNR), Messina 98164, Italy; 🇮🇹 Messina, Italy