Abstract: An example of an apparatus to infer joint rotations and positions is provided. The apparatus includes a communications interface to receive raw data from an external source. The raw data includes a first joint position and a second joint position of an input skeleton. In addition, the apparatus includes a memory storage unit to store the raw data. Furthermore, the apparatus includes a pre-processing engine to generate normalized data from the raw data. The normalized data is to be stored in the memory storage unit. Also, the apparatus includes an inverse kinematics engine to apply a neural network to infer a joint rotation from the normalized data. The neural network is to use historical data. Training data used to train the neural network includes positional noise.

Abstract: System and method for extracting human pose information from an image, comprising a feature extractor connected to a database, a convolutional neural network (CNN) with a plurality of CNN layers. Said system/method further comprising at least one of the following modules: a 2D body skeleton detector for determining 2D body skeleton information from the human-related image features; a body silhouette detector for determining body silhouette information from the human-related image features; a hand silhouette detector for determining hand silhouette detector from the human-related image features; a hand skeleton detector for determining hand skeleton from the human-related image features; a 3D body skeleton detector for determining 3D body skeleton from the human-related image features; and a facial keypoints detector for determining facial keypoints from the human-related image features.

Abstract: An example of an apparatus for markerless motion capture is provided. The apparatus includes cameras to capture images of a subject from different perspectives. In addition, the apparatus includes a pose estimation engines to receive the images. Each pose estimation engine is to generate a coarse skeletons of the received image and is to identify a region of the image based on the coarse skeleton. Furthermore, the apparatus includes pose estimation engines to receive the regions of interest previously identified. Each of these pose estimation engines is to generate a fine skeleton of the region of interest. In addition, the apparatus includes attachment engines to generate a whole skeletons. Each whole skeleton is to include a fine skeleton attached to a coarse skeleton. The apparatus further includes an aggregator to receive the whole skeletons. The aggregator is to generate a three-dimensional skeleton from the whole skeletons.

Abstract: An example of an apparatus for markerless motion capture is provided. The apparatus includes cameras to capture images of a subject from different perspectives. In addition, the apparatus includes a pose estimation engines to receive the images. Each pose estimation engine is to generate a coarse skeletons of the received image and is to identify a region of the image based on the coarse skeleton. Furthermore, the apparatus includes pose estimation engines to receive the regions of interest previously identified. Each of these pose estimation engines is to generate a fine skeleton of the region of interest. In addition, the apparatus includes attachment engines to generate a whole skeletons. Each whole skeleton is to include a fine skeleton attached to a coarse skeleton. The apparatus further includes an aggregator to receive the whole skeletons. The aggregator is to generate a three-dimensional skeleton from the whole skeletons.

Abstract: Neuromodulation devices and methods of their use are described in which a therapeutic device is configured to generate a treatment for treating pain such as the reduction of the symptoms of chronic and acute pain as well as for treating other conditions. The neuromodulation device generates an output electrical signal in the form of pulses with a fast rise-time spike waveform followed by a longer-duration, lower amplitude primary phase waveform. The output signal includes a broad range of frequency components, with time constants tuned so as to interact with specific cell membrane or cellular components. The output signal may be conducted to the patient via electrodes. The pulses are triggered at variable intervals which prevent habituation.

Abstract: This disclosure describes an activity recognition system for asymmetric (e.g. left- and right-handed) activities that leverages the symmetry intrinsic to most human and animal bodies. Specifically, described is 1) a human activity recognition system that only recognizes handed activities but is inferenced twice, once with input flipped, to identify both left- and right-handed activities and a training method for learning-based implementations of the aforementioned system that flips all training instances (and associated labels) to appear left-handed and in doing so, balances the training dataset between left- and right-handed activities.

Abstract: This disclosure describes an activity recognition system for asymmetric (e.g. left- and right- handed) activities that leverages the symmetry intrinsic to most human and animal bodies. Specifically, described is 1) a human activity recognition system that only recognizes handed activities but is inferenced twice, once with input flipped, to identify both left- and right-handed activities and a training method for learning-based implementations of the aforementioned system that flips all training instances (and associated labels) to appear left-handed and in doing so, balances the training dataset between left- and right-handed activities.