Measurement unit and monitoring system for monitoring indicator of Parkinson's disease in person

A monitoring system comprising:

• an electrode patch comprising:
• measurement electronics positioned on the electrode patch configured for continuously measuring an electromyography (EMG) signal from only a single limb of a person comprising:
• measurement electrodes configured to be positioned parallel to muscle fibers of the limb, and
• a reference electrode configured to be placed on an inactive muscle area of the limb,
• a motion sensor configured to be attached to the limb for measuring a motion signal from the limb,
• a processing unit configured to:
• select representative time segments of the EMG signal and the motion signal representing muscle activities measured during static and dynamic contractions;
• determine the principal component representation of the EMG signal from the representative time segments of the EMG signal and the motion signal in real time, before transmission, by:
• extracting the at least one feature of the EMG signal and extracting the at least one feature of the motion signal;
• forming a feature vector on the basis of the at least one extracted feature of the EMG signal and the at least one extracted feature of the motion signal;
• forming an initial sample correlation matrix from EMG and motion signals of a population;
• and
• updating the initial sample correlation matrix in a time recursive manner by forming a new sample correlation matrix on the basis of values of the extracted features and the initial sample correlation matrix;
• wherein the principal component representation represents a projection of at least one feature of the EMG signal and at least one feature of the motion signal into at least one uncorrelated feature in a feature space formed by orthogonal basis vectors;
• and
• a transceiver unit configured to transmit the principal component representation to an analysis unit;
• the analysis unit configured to receive the principal component representation of the EMG signal and the motion signal as a function of time and determine a value of an indicator of Parkinson's Disease based on the principal component representation;
• wherein a range of fluctuation of the principal component representation represents a range of magnitude of the person's symptoms;
• and
• wherein a value of the principal component representation above a mean of the principal component representation represents a first number of disease symptoms, and a value of the principal component representation below the mean of the principal component representation represents a second number of disease symptoms lower than the first number of symptoms.