About this trial
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.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
healthy male and female aged 60 years and older
signing of informed consent
Disqualifiers
chronic diseases
cardiovascular disease
presence of dementia and/or depression
presence of confirmed paranoid or psychotic symptoms
Trial population
The elderly population plays a significant role in society, influencing social, economic, and cultural aspects. Intellectual stimulation and social interactions are crucial for keeping their minds active and preventing isolation, decline and depression. Physical activity can help to maintain strength and balance, preventing motor decline and reducing the risk of falls and injuries. Issues such as loss of intrinsic abilities, exposure to adversity, and functional deterioration can cause psychological distress. Common concerns among the elderly include health changes, loss of loved ones, income reduction, and a diminished sense of purpose after retirement. A proactive approach to health management and a strong support system can significantly enhance the overall well-being of the elderly.
Trial design
Cohort
Prospective
Treatments tested in this trial
Noninvasive wearable devices (smartwatch and heart rate monitor band)
Other interventionEach enrolled subject will be equipped with noninvasive wearable devices (smartwatch and heart rate monitor band) to monitor physiological parameters and emotional states related to anxiety and stress. Each subject will be required to wear the smartwatch on his or her wrist for the duration of the study, about 3-6 months; while the heart rate monitor band will be worn for about 10 minutes a day. At the same time, a mobile application, RESILIENT, will be developed and implemented to serve as the main interface for self-assessment data entry and for feedback and recommendations. The psycho-physical condition of each subject will be monitored by the app through customized and contextualized mental exercises based on daily activities. This approach will test the effectiveness of the proposed architecture in reducing unhealthy habits and promoting health and wellness recommendations
Treatment groups
Trial outcomes
Primary outcomes
Heart Rate(HR)
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)
The chest strap Polar H10 measures the time intervals between successive heart beats and calculates Heart Rate Variability (HRV) in milliseconds (ms).
Facial emotion recognition
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.
Steps taken
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.
Sponsors and contacts
Click on the lead sponsor to view all of their trials.