Wellness Assessment of Alzheimer’s Patients in an Instrumented Health-Care Facility

Abstract

Wellness assessment refers to the evaluation of physical, mental, and social well-being. This work explores the possibility of applying technological tools to assist clinicians and professionals to improve the quality of life of people through continuous monitoring of their wellness. The contribution of this paper is manifold: a coarse-grained localization system is responsible for monitoring and collecting data related to patients, while a novel wellness assessment methodology is proposed to extract quantitative indicators related to the well-being of patients from the collected data. The proposed system has been installed at “Il Paese Ritrovato", an innovative health-care facility for Alzheimer’s in Monza, Italy; first satisfactory results have been obtained, and the dataset shows great potential for several applications.

Alzheimer’s Garden: Understanding Social Behaviors of Patients with Dementia to Improve Their Quality of Life

“…A monitoring system, previously implemented by Masciadri et al [ 14 ], collects residents’ localization data through a Received Signal Strength Indicator (RSSI) based smart wearable bracelet every 10 seconds and stores the history of visited areas inside the village for every resident into a database at the end of each day [ 14 ]. Residents are informed about the localization system, and gave the rights to La Meridiana Due who is responsible for the data collection and treatment process.…”

“…Assessing residents’ wellbeing, specifically their social behavior, only through their localization data is a hard task. We resort to the Relational Index [ 14 ]: an indicator that aims to estimate the degree of relation between persons i and j on day d taking into account the amount of time they spend together in the same place. We extend it by introducing the Individual Relational Index for person i on day d : where is the set of active users on day d .…”

“…In this work, we analyzed localization data to gather insights on the behavior of the residents of Il Paese Ritrovato to design solutions for the improvement of their social life and wellbeing. We extended the notion of Relational Index [ 14 ] to single individuals and investigated its statistical correlation with other variables by means of a linear regression and a independence test , observing and explaining why it is influenced by all of them except for the weather. We also examined the popularity of different areas of the facility by leveraging functional k-means clustering and functional principal component analysis , identifying well-functioning social areas and those in need of enhancements, such as the outdoor places.…”

Understanding Social Behaviour in a Health-Care Facility from Localization Data: A Case Study

“…We propose the Community behaviour Prediction Table (CBPT) (see Figure 5), a visual tool combining the predictive models to support caregivers in organizing activities at Il Paese Ritrovato. This table provides the predicted value of the Community Time-Specific RI and the PI for each place for three times of the day: morning (8)(9)(10)(11)(12), noon (12)(13)(14)(15) and afternoon (15)(16)(17)(18)(19)(20). One of the possible ways to use the CBPT is to first observe the Community RI prediction and filter out the activities not suitable for its value.…”

“…Beds are equipped with pressure sensors located beneath the mattress, which can detect whether a patient is lying or sitting on it. Most importantly, a localization system, introduced by Masciadri et al [ 13 ], allows to track the position of the patients through the use of multiple Bluetooth antennas scattered around the facility and Bluetooth wristbands are worn by the patients. One of the critical issues of the system is the tendency of the patients to reject the wristbands.…”