[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100553799":3},{"organization":4,"outcomesModule":7,"designInfo":29,"detailedDescription":28,"studyPopulation":32,"armGroups":33,"interventions":39,"overallOfficials":44,"centralContacts":48,"locations":56,"responsibleParty":85,"collaborators":28,"id":87,"slug":28,"hasResults":88,"nctId":89,"briefTitle":90,"officialTitle":91,"acronym":92,"eligibilityCriteria":93,"healthyVolunteers":94,"sex":95,"minAge":96,"maxAge":28,"enrollmentInfo":97,"targetDuration":28,"studyType":100,"phases":28,"briefSummary":101,"conditions":102,"keywords":105,"overallStatus":59,"whyStopped":28,"lastUpdateSubmitDate":111,"lastUpdatePostDateStruct":112,"startDateStruct":115,"completionDateStruct":117,"leadSponsor":119,"locationsCount":120},{"fullName":5,"class":6},"Istituto per la Ricerca e l'Innovazione Biomedica","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":28,"otherOutcomes":28},[9,13,16,19,22,25],{"measure":10,"description":11,"timeFrame":12},"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).","Through study completion, an average of 1 year",{"measure":14,"description":15,"timeFrame":12},"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).",{"measure":17,"description":18,"timeFrame":12},"Facial emotion recognition","The smartphone's camera records facial expressions in order to evaluate and quantify human emotions.\n\nThe 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.",{"measure":20,"description":21,"timeFrame":12},"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.",{"measure":23,"description":24,"timeFrame":12},"Distance traveled","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).",{"measure":26,"description":27,"timeFrame":12},"Calories burned","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.",null,{"allocation":28,"interventionModel":28,"interventionModelDescription":28,"primaryPurpose":28,"observationalModel":30,"timePerspective":31,"maskingInfo":28},"COHORT","PROSPECTIVE","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.",[34],{"label":35,"type":28,"description":36,"interventionNames":37},"healthy elderly","The sample consists of healthy elderly volunteers who will wear noninvasive wearable devices (smartwatch and heart rate monitor band) to monitor physiological parameters and emotional states related to anxiety and stress.",[38],"Other: Noninvasive wearable devices (smartwatch and heart rate monitor band)",[40],{"type":6,"name":41,"description":42,"armGroupLabels":43,"otherNames":28},"Noninvasive wearable devices (smartwatch and heart rate monitor band)","Each 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.\n\nThe 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",[35],[45],{"name":46,"affiliation":5,"role":47},"Gennaro Tartarisco","PRINCIPAL_INVESTIGATOR",[49,53],{"name":46,"role":50,"phone":51,"phoneExt":28,"email":52},"CONTACT","+393283377046","gennaro.tartarisco@irib.cnr.it",{"name":54,"role":50,"phone":28,"phoneExt":28,"email":55},"Maria Valeria Maiorana","mariavaleria.maiorana@irib.cnr.it",[57],{"facility":58,"status":59,"city":60,"state":28,"zip":61,"country":62,"countryCode":63,"cosmosGeoPoint":64,"geoPoint":69,"contacts":70},"Institute for Biomedical Research and Innovation (IRIB)-National Reasearch Council (CNR), Messina 98164, Italy","RECRUITING","Messina","98164","Italy","IT",{"type":65,"coordinates":66},"Point",[67,68],15.55256,38.19394,{"lat":68,"lon":67},[71,74,75,78,80,82,83],{"name":72,"role":50,"phone":28,"phoneExt":28,"email":73},"Serena Iacono Isidoro","serena.iaconoisidoro@irib.cnr.it",{"name":46,"role":47,"phone":28,"phoneExt":28,"email":28},{"name":76,"role":77,"phone":28,"phoneExt":28,"email":28},"Rosanna Turrisi","SUB_INVESTIGATOR",{"name":79,"role":77,"phone":28,"phoneExt":28,"email":28},"Simona Campisi",{"name":81,"role":77,"phone":28,"phoneExt":28,"email":28},"Roberta Bruschetta",{"name":72,"role":77,"phone":28,"phoneExt":28,"email":28},{"name":84,"role":77,"phone":28,"phoneExt":28,"email":28},"Gaspare Cusimano",{"type":47,"investigatorFullName":46,"investigatorTitle":86,"investigatorAffiliation":5,"oldNameTitle":28,"oldOrganization":28},"Head of Unit","100553799",false,"NCT06490783","Cyber-Human Systems for Personalized Well-being and Health","CybeR-human systEms for perSonalIzed mentaL and physIcal wEll-beiNg and Health","RESILIENT","Inclusion Criteria:\n\n* healthy male and female aged 60 years and older\n* signing of informed consent\n\nExclusion Criteria:\n\n* chronic diseases\n* cardiovascular disease\n* presence of dementia and\u002For depression\n* presence of confirmed paranoid or psychotic symptoms",true,"ALL","60 Years",{"count":98,"type":99},10,"ESTIMATED","OBSERVATIONAL","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\u002Finteraction, 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.",[103,104],"Geriatric Health Services","Health Services for the Elderly",[106,107,108,109,110],"elderly","wellbeing","Artificial Intelligence","quality of life","AI","2025-04-29",{"date":113,"type":114},"2025-05-01","ACTUAL",{"date":116,"type":114},"2024-07-01",{"date":118,"type":99},"2026-05-31",{"name":5,"class":6},1]