AMBIENT ASSISTED LIVING SYSTEMS

Acitive & Healthy Ageing

Ambient Assisted Living (AAL) are concepts, products and services which combine new technologies and the social environment in order to improve quality of life in all periods of life. This multi-disciplinary field aims at providing an ecosystem of different types of sensors, computers, mobile devices, wireless networks and software applications for personal healthcare monitoring and telehealth systems.
Strategies for Active & Healthy Ageing, taking advantage of the Internet of Things potential, allow people to have the opportunity to live a long and healthy life providing appropriate and high-quality home-based health care and social services.

In this contest, our research activity aims to provide important support to people, self-sufficient or partially self-sufficient with limited comorbidities, who are looking for safe and comfortable environments where to live. The idea is to create a platform that integrates a series of modules (e.g.: safety, functional exercise, cognitive exercise, social and e-commerce) each aimed at a specific aspect of the AAL. The modules are independent; the end-user can provide himself with one or a combination of them, according to his needs. Our activity focuses on the safety module development by using Microsoft Kinect systems whose output are exploited by Artificial Intelligence algorithms for the identification of potentially dangerous situations (Figure 1). In addition, these Microsoft Kinect systems could be integrated with a network of ambient sensors in order to better reconstruct the scenario in which the monitored subject moves (Figure 2).

Wearable and Modular Inertial Motion Unit

Measuring human movement has many useful applications ranging from fall risk assessment, to quantifying sports exercise, studying people habits and monitoring the elderly. We developed a versatile, wearable device based on a 9-degrees-of-freedom inertial measurement unit conceived for providing objective measurements of trunk or limb movements for the assessment of motor and balance control abilities. The proposed device measures linear accelerations, angular velocities and heading and can be configured to either wirelessly transmit the raw or preprocessed data to a computer for online use, e.g. visualization or further processing, or to store the acquired data locally for long term monitoring during free movement. Further, the device can work in either single sensor or multiple sensors configuration, to simultaneously record several body parts for monitoring full body kinematics.

In collaboration with Laboratorio Microcalcolatori e Strumentazione Elettromedicale (Ing. Cristiani A., Ing. Bertolotti G.M.)

BIOMEDICAL INSTRUMENTATION

Functional Head Impulse Test (fHIT)

Peripheral vestibular function may be tested quantitatively by measuring the gain of the rotational vestibulo-ocular reflex (eye velocity/head velocity), or functionally, by assessing how well the rotational vestibulo-ocular reflex (rVOR) per-forms with respect to its goal of stabilizing gaze in space. We developed a functional head impulse testing device (fHIT) based on an inertial sensing system allowing to investigate the functional performance of the rVOR by testing its gaze stabilization ability, independently from the subject’s visual acuity, in response to head impulses at different head angular accelerations ranging from 2000 to7000 deg/s². The system assesses the ability of the patient to read an optotype briefly presented during head rotation. The outcome of the test is the percentage of correctly read optotypes at different head accelerations. Thus, vestibular function can be assessed without measuring eye movements.

In order to find the relation between the functional (percentage of reading) and quantitative (gain) measure and to understand the role of corrective saccades, we also developed a new software and hardware research tool allowing the combined measurement of eye and head movements, together with the timing of the optotype on screen, based on the EyeSeeCam system.

FUNDED PROJECTS:

TheDALUS – The Disable Assisted Living for University Students (id 379357, Regione Lombardia)
PRIN 2010R277FT A quantitative multifactorial approach to the assessment and prevention of falls in the elderly – Research unit responsible.

MAIN COLLABORATIONS:

DaisyLabs – PMI of the Pavia Technology Pole.
Agevoluzione – PMI of the Pavia Technology Pole.
SAISD – Centro Servizio di Ateneo Assistenza ed integrazione studenti disabili e con DSA , Università di Pavia.
Dipartimento di Scienze del Sistema Nervoso e del Comportamento, University of Pavia.
Dipartimento di Sanità Pubblica, Medicina Sperimentale e Forense, University of Pavia.
Prof. David. S. Zee, Dept. of Neurology, The Johns Hopkins School of Medicine, Baltimore, MD, USA.
Prof. Dominik Straumann, Dept. of Neurology, Zurich University Hospital, Zurich, Switzerland.