Alzheimer’s disease (AD) is the most frequent form of dementia, hindering independence and memory and causing a progressive withdrawal from family and society. The more the patients are isolated, the faster the disease progresses. Therefore, engaging patients in social activities and encouraging them to build and maintain strong relationships is crucial to preserve their independence and provide them with a better quality of life. We collaborate with Il Paese Ritrovato (The Rediscovered Village), the first AD assisted care home in the form of a village ever built in Italy, managed by La Meridiana. A localization system allows to track the position of the patients through the use of Bluetooth antennas and wristbands worn by the residents. Our project, Alzheimer’s Garden (ALZGAR), aims to understand the social behavior of AD patients living in Il Paese Ritrovato and to promote sociability among them to improve their quality of life and slow down the progression of the disease. By analyzing the data collected through the existing localization system, we gain insight into the behavior of the residents to guide the design of novel space organizations and propose activity scheduling solutions, ultimately promoting socialization. We introduce objective indexes to measure sociability and attendance of places, as none are available in the literature. We outline the patients’ social profiles and draw the social network of the village. We determine the correlation
between sociability and possible influencing factors, observing that the weather does not affect the sociability of the residents, being most facilities indoors, whereas other factors such as the season and the patient’s bedroom floor do play an important role. To assess the utilization and social utility of social places, we analyze where residents spend their time in the village, identifying highly frequented areas, such as the cinema, and unpopular ones, such as the garden.
Considering the statistical and architectural analyses we carried out and the thorough state-of-the-art knowledge on AD-sensitive architecture, we propose predictive tools and architectural interventions. We propose the Community Behavior Prediction Table, a visual tool leveraging predictive models to support caregivers in organizing activities, along with extensive analyses and examples on how to leverage this tool to schedule state-of-the-art, AD-designed activities. This tool can prove to be valuable for the caregivers of Il Paese Ritrovato, since the compatibility of an activity with the location it is held at and the social profiles of the participants engaged is crucial to guarantee therapeutic benefits to the dwellers.
PRINCIPAL ACADEMIC TUTOR
Sara Comai, Dipartimento di Elettronica, Informazione e Bioingegneria – Politecnico di Milano
OTHER ACADEMIC TUTOR
Andrea Masciadri, Dipartimento di Elettronica, Informazione e Bioingegneria – Politecnico di Milano
Cooperativa La Meridiana Il Paese Ritrovato
Alberto Attanasio, Cooperativa La Meridiana
Gloria Bellini, Mathematical Engineering Politecnico di Milano
Nicola De Angeli, Computer Science and Engineering Politecnico di Milano
Marco Cipriano, Computer Engineering Politecnico di Torino
Jacopo Pio Gargano, Computer Science and Engineering Politecnico di Milano
Matteo Gianella, Mathematical Engineering Politecnico di Milano
Gianluca Goi, Architecture Built Environment Interiors Politecnico di Milano
Gabriele Rossi, Management Engineering Politecnico di Milano