Abstract: A system and method for remote monitoring of patient motor functions includes a computing device that uses captured image data depicting a patient's body part and, based on movement information, detects whether a condition may exist that is affecting motor functions. The body part can be a hand that is tracked as the user performs a tapping exercise. The body part can also include the patient's face during speech and also without speech.

Abstract: A cloud or other network-based multimodal dialogue system is used to conduct automated screening interviews by engaging with conversational AI over a device of the user's choice (smartphone, tablet, laptop) from the comfort of their home. A screening interview will typically guide a user to blow towards a microphone, use signals from the microphone to calculate amplitudes, and use the amplitudes to calculate a flow rate and a flow volume. Contemplated systems and methods can be deployed in an automatically scalable cloud environment allowing it to serve an arbitrary number of end users at a very small cost per interaction. No special devices unique to the task are needed, which makes the technology accessible to a vast number of users.

Abstract: A virtual agent instructs a responding person to perform specific verbal exercises. Audio and image inputs from the responding person's performance of the exercises are used to identify speech, video, cognitive, and/or respiratory biomarkers, which are then used to evaluate speech motor function and/or neurological health. Contemplated exercises include test aspects of oral motor proficiency, sustained phonation, diadochokinesis, reading speech, spontaneous speech, spirometry, picture description, and emotion elicitation. Metrics from evaluation of the responding person's performance are advantageously produced automatically, and are presented in spreadsheet format.

Abstract: A computer-generated dialog session is customized for a user having a pathology characterized at least in part by a speech pathology. The user's speech is analyzed for spans of speech in which the starts and ends of the spans satisfy predetermined thresholds of time. Customization occurs by altering at least one of the following configurable parameters: (a) a threshold minimum signal strength of speech (dB) to consider as the start of the span of speech; (b) an adjustment factor by which signal strengths of background noise increases between consecutive spans of speech; (c) a threshold between signal strength during the span of speech and signal strength during the span of non-speech; (d) a start speech time threshold; and (e) an end speech time threshold.