The aim of the present work is the development of a sensing platform constituted by wearable sensors endowed with an App devoted to execute rehabilitation protocol for the treatment of a large number of musculo-skeletal diseases. Through the wearable sensors, mainly inertial (IMU) and e-textile sensors (KPF), a Decision Support System (DSS) included in the App will assist the patient in performing personalized rehabilitation exercises designed by physician/therapist. The App, developed in two different interfaces for professional and patient, allows to remotely supervise and train the execution of user rehabilitation task by means of data stored in a clinical server. The platform can give assistance to the patient allowing to correctly perform the exercise and to correct wrong movements in real time. Therefore this system is capable to provide a complete set of information, alerts and strategies that are used by the patient to control symptoms, slow down the disease progression and achieve optimum physical function.

This paper presents an innovative wearable kinesthetic glove realized with knitted piezoresistive fabric (KPF) sensor technology. The glove is conceived to capture hand movement and gesture by using KPF in a double-layer configuration working as angular sensors (electrogoniometers). The sensing glove prototype is endowed by three KPF goniometers, used to track flexion and extension movement of metacarpophalangeal joint of thumb, index, and middle fingers. The glove is devoted to the continuous monitoring of patients during their daily-life activities, in particular for stroke survivors during their rehabilitation. The prototype performances have been evaluated in comparison with an optical tracking system considered as a gold standard both for relieving static and dynamic posture and gesture of the hand. The introduced prototype has shown very interesting figures of merit. The angular error, evaluated through the standard Bland Altman analysis, has been estimated in ±3° which is slightly less accurate than commercial electrogoniometers. Moreover, a new conceptual prototype design, preliminary evaluated within this study, is presented and discussed in order to solve actual limitations in terms of number and type of sensor connections, avoiding mechanical constraints given by metallic inextensible wires and improving user comfort.

In this paper, we report on a new technology used to implement strain sensors to be integrated in usual garments. A particular conductive mixture based on commercial products is realized and directly spread over a piece of fabric, which shows, after the treatment, piezoresistive properties, i.e., a change in resistance when it is strained. This property is exploited to realize sensorized garments such as gloves, leotards, and seat covers capable of reconstructing and monitoring body shape, posture, and gesture. In general, this technology is a good candidate for adherent wearable systems with excellent mechanical coupling with body surface. Here, we mainly focused on a sensorized glove able to detect posture and movements of the fingers. It could be used in several fields of application. We report on experimental results of a sensorized glove used as movements recorder for rehabilitation therapies and medicine. Furthermore, we describe a dedicated methodology used to read the output sensors which allowed to avoid using metallic wires for the connections. The price to be paid for all these advantages is a nonlinear electric response of the fabric sensor and a too long settling time, that in principle, make these sensors not suitable for real-time applications. Here we propose a hardware and computational solution to overcome this limitation.

We consider the problem of maximizing the localization accuracy of a mobile vehicle, based on triangulation measurements derived from optical data. The problem is intrinsically nonlinear, as the linear approximation of the system is not observable. This implies that the choice of inputs (i.e., the path followed) may affect the quality of observations made, and ultimately the localization accuracy. We consider the problem of finding the most informative exploratory path of the given length for a rover (modeled as a point in the plane) with optical triangulation information.