System configured to monitor the motor activity of a person’s lower limbs
Wearable sensor system for home monitoring of involuntary walking blocks of patients suffering from neurophysiological diseases (such as Parkinson’s). The devices cooperate in a Master-Slave configuration to record and process information in real-time, signalling the possible occurrence of the block that could cause a fall.
The hardware consists of two wearable devices to be fixed on the legs, which include sensors, memory, computing and wireless communication units, and a battery. One acts as a Master the other as a Slave: data acquisition takes place in parallel, but processing takes place only on the Master, which wirelessly receives the data from the Slave, processes these together with other captured data, stores them in its memory and transmits the data wirelessly to an external computer for off-line processing and sharing of the electronic diary in the cloud. The algorithms robustly recognise specific motor symptoms, such as involuntary blocking, in real-time. This ensures that the patient can be promptly sent sensory feedback which, according to clinical studies, can help him to relax the state of involuntary block, preventing the fall. Motor symptom data is stored on the built-in memory by creating an electronic diary. To increase the battery life, an algorithm is implemented that recognises the sitting and lying positions, bringing the components to stand-by.
- Collection of objective motor information for a long time and during everyday life;
- Monitoring of patients on a large territorial, social and environmental scale can find application in a statistical tool for epidemiological study relating to specific diseases;
- Smart Health technologies related to the Internet of Things.
- Daily home monitoring, better definition of the clinical picture;
- Reduction of hospitalisations for falls or trauma;
- Rationalisation of costs related to the use of medical staff and drugs.