The adoption of motor-rehabilitative therapies is highly demanded in a society where the average age of the population is constantly increasing. A recent trend to contain costs while providing high quality of healthcare services is to foster the adoption of self-care procedures, performed primarily in patients’ environments rather than in hospitals or healthcare structures, especially in the case of intensive and chronic patients’ rehabilitation. This work presents a platform to enhance limb functional recovery through telerehabilitation sessions. It relies on a sensing system based on inertial sensors and data fusion algorithms, a module to provide bio-feedback tailored to the users, and a module dedicated to the physicians’ practices. The system design had to face several cyber-physical challenges due to the tight interaction between patient and sensors. For instance, integrating the body kinematics into the sensory processing improved the precision of measurements, simplified the calibration procedure, and made it possible to generate bio-feedback signals. The precision of the proposed system is presented through a set of experiments, showing a resolution below one degree in monitoring joint angles. A validation of the proposed solution has been performed through a medical trial on 50 patients affected by osteo-articular diseases. The presented framework has been designed to operate in other application fields, such as neurological rehabilitation (e.g., Parkinson, Stroke, etc.), sports training, and fitness activities.

No abstract

Tracking the position and the orientation of human limbs to reconstruct postures and actions is becoming a crucial need in several application domains, including medicine, rehabilitation, sport, and games. However, most available solutions are expensive, imprecise, or require an instrumentation of the environment. This paper presents a low-cost tracking system based on a set of wearable inertial measurement units (IMUs) coordinated as a wireless body area network. After the system description, the characterization of the single node is provided through a set of experiments. Issues related to real-time processing, calibration, data synchronization, and energy consumption are introduced using a preliminary simplified setup with two nodes

No abstract

Wearable devices are driving the development of post-surgery rehabilitation procedures, also helping in reducing the recovery time and social costs. This paper presents a real-time monitoring framework aimed at supporting telerehabilitation sessions for lower-limbs functional recovery. The presented framework supports patients during the execution of rehabilitation exercises by monitoring the limb movements through a set of low-cost wearable sensors and providing them with multi-modal bio-feedback to enhance the quality of the performed actions. The system also assists the therapist in the definition of exercises tailored to the patient and enables the collection of historical data in cloud-based services for monitoring the effects of therapies and further analysis.