Abstract: The present invention relates to a light-weight, small and portable ambulatory sensor for measuring and monitoring a person's physical activity. Based on these measurements and computations, the invented system quantifies the subject's physical activity, quantifies the subject's gait, determines his or her risk of falling, and automatically detects falls. The invention combines the features of portability, high autonomy, and real-time computational capacity. High autonomy is achieved by using only accelerometers, which have low power consumption rates as compared with gyroscope-based systems. Accelerometer measurements, however, contain significant amounts of noise, which must be removed before further analysis. The invention therefore uses novel time-frequency filters to denoise the measurements, and in conjunction with biomechanical models of human movement, perform the requisite computations, which may also be done in real time.

Abstract: A sensorimotor rehabilitation system can analyze body movement kinematics of a person, and in particular analyze the use of limbs (e.g., upper limbs) to provide feedback for sensorimotor rehabilitation. Parameters of body movement (e.g., quantity and type of body movement) can be assessed based on data recorded from an inertial sensor affixed or connected to, for example, an upper limb of a person or outer clothing such as a sleeve. Automated feedback can be provided to the user to improve sensorimotor rehabilitation.

Abstract: A system is provided for monitoring whether a user is wearing and/or using a tagged device such as prescribed footwear, a walking aid, a brace or other orthotics. The system may detect whether the user is using a tagged device and can, in some embodiments, alert the user or the user's caregivers if the user ambulates without using the tagged device.

Abstract: A method for myoelectric-based processing of speech. The method includes capturing a myoelectric signal from a user using at least one electrode, wherein the electrode converts an ionic current generated by muscle contraction into an electric current. The method also includes amplifying the electric current, filtering the amplified electric current, and converting the filtered electric current into a digital signal. The method further includes transmitting the myoelectric signal to a digital device, transforming the digital signal into a written representation using an automatic speech recognition method, and generating an audible output from the written representation using a speech synthesis method.