Patent US10083233 AI Biotech/Diagnostics: Other Innovation

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Patent US10083233

Issued 2018-09-25

Video Processing For Motor Task Analysis

Video processing for motor task analysis is described. In various examples, a video of at least part of a person or animal carrying out a motor task, such as placing the forefinger on the nose, is input to a trained machine learning system to classify the motor task into one of a plurality of classes. In an example, motion descriptors such as optical flow are computed from pairs of frames of the video and the motion descriptors are input to the machine learning system. For example, during training the machine learning system identifies time-dependent and/or location-dependent acceleration or velocity features which discriminate between the classes of the motor task. In examples, the trained machine learning system computes, from the motion descriptors, the location dependent acceleration or velocity features which it has learned as being good discriminators. In various examples, a feature is computed using sub-volumes of the video.

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3 Independent Claims

1. A computer-implemented method comprising: receiving a video depicting at least part of a user performing a motor task; redacting features from the video which may identify the user; inputting the video to a trained machine learning system, the trained machine learning system having been trained to detect multiple sequences of location-dependent local motion features of videos which discriminate among a plurality of classes of the motor task; and receiving, from the trained machine learning system, a label identifying a motor task class of the plurality of classes, the plurality of classes including an indication of a performance level of the motor task based on at least one of the multiple sequences of location-dependent local motion features in the video detected by the trained machine learning system.
16. A computer storage media storing instructions comprising: instructions to receive a video depicting at least part of a person or animal performing a motor task; instructions to input the video to a trained machine learning system, having been trained to detect multiple sequences of location-dependent local acceleration features of videos which discriminate among a plurality of classes of the motor task, the local acceleration features calculated by taking into account frequency of change of direction of rate of change of optical flow values of a sub-volume of the video; and instructions to receive, from the trained machine learning system a label identifying a motor task class of the plurality of classes, wherein the plurality of classes includes an indication of a performance level of the motor task based on at least one of the multiple sequences of location-dependent local motion features in the video detected by the trained machine learning system.
17. A motor-task classifier comprising: a trained machine learning system, having been trained to detect multiple sequences of location-dependent local motion features of videos which discriminate among a plurality of classes of a motor task, the training comprising optimizing a criteria based at least in part on a duration of a sub-volume; and a processor arranged to: compute motion descriptors from a video; input the motion descriptors to the trained machine learning system; and receive, from the trained machine learning system, a label identifying a motor task class of the plurality of classes, wherein the plurality of classes includes an indication of a performance level of the motor task based on at least one of the multiple sequences of location-dependent local motion features in the video detected by the trained machine learning system.