Abstract: An analysis method for the causal inference of human physiological network in multiscale time series signals includes the following steps: S1: decomposing physiological signals u1, u2, . . . , um to be analyzed by using a noise-assisted multivariate empirical mode decomposition (NA-MEND) algorithm; S2: carrying out a causal analysis between two different physiological signals ui, uj, where i=1, 2, . . . , m, j=1, 2, . . . , m, and i?j, to obtain a causality between the two signals; and S3: repeating step S2 for any two signals in u1, u2, . . . , um until a causality between each two signals in u1, u2, . . . , um is obtained to form the causal network. The present invention can effectively analyze the causal network of the physiological signals, thereby facilitating the application of the physiological signals.

Abstract: The invention provides a monitoring apparatus (1) for an ambulatory subject (2) that includes a portable monitor (3) mountable on subject (3) that includes an accelerometer that determines the instant acceleration of subject (2) in one or more determined directions. It further includes a processing unit (7) that determines at least one instant ambulatory performance indicia of subject (2) from the determined instant acceleration, determines at least one designated performance threshold from at least one previously determined instant ambulatory performance indicia and initiates an event under predetermined conditions that is communicated to remote receiver (5) for the attention of carer (11), providing remote monitoring and supervision of subject (2) based on ambulatory performance of subject (2).