Abstract: Method(s) and apparatus are provided for interfacing with a nervous system of a subject.

Abstract: Method(s) and apparatus are provided for interfacing with a nervous system of a subject.

Abstract: Method(s) and apparatus are provided for operating and training an autoencoder. The autoencoder outputs a latent vector of an N-dimensional latent space for classifying input data. The latent vector includes a label vector y and a style vector z. The style vector z is regularised during training for effecting time invariance in the set of label vectors y associated with the input data. Method(s) and apparatus are further provided for controlling the optimisation of an autoencoder. The autoencoder outputting a latent vector of an N-dimensional latent space for classifying input data. The latent vector comprising a label vector y and a style vector z. The regularisation of the style vector z is controlled to increase or decrease the time invariance of the label vectors y. An autoencoder configured based on the above-mentioned trained autoencoder that regularised the style vector z for effecting time invariance in the set of label vectors y associated with the input data during classification.

Abstract: Herein described is an osseointegrated interface device for engagement with an amputated limb including the skin comprising: a cap portion engageable with an osseointegrated device; wherein the cap portion comprises a surrounding flange; and wherein in use the surrounding flange receives the skin of the amputated limb at a distance spaced from the osseointegrated device.

Abstract: Systems, apparatus, and method(s) are provided for automatically detecting and/or estimating one or more clinical biomarker(s) of a subject. Sensor data is received from one or more sensor(s) associated with the subject. The sensor data is using a first set of machine learning (ML) model(s) configured to extract portions of sensor data relevant for estimating one or more clinical biomarker(s) of the subject. The extracted portions of sensor data from sensors associated with the subject are processed to determine one or more clinical biomarkers. The processing of the received extracted portions of sensor data includes using a second set of ML model(s) configured to estimate the one or more clinical biomarker(s) of the subject. The portions of sensor data may comprise the first set of ML model(s) being configured to extract segments of sensor data and classify the segments of sensor data based on one or more clinical biomarker components for use in the estimation of one or more clinical biomarkers of interest.

Abstract: A system for controlling a cardiac system of a subject comprising: a plurality of sensors arranged to detect physiological activity in a subject and produce physiological signals corresponding to the detected physiological activity; at least one controller arranged to receive the physiological signals and to process the physiological signals using at least one model to determine at least one output signal; and a plurality of neural stimulators arranged to receive the at least one output signal and to provide neural stimulation to the nervous system of the subject based on the at least one output signal.

Abstract: Herein described is an osseointegrated interface device for engagement with an amputated limb including the skin comprising: a cap portion engageable with an osseointegrated device; wherein the cap portion comprises a surrounding flange; and wherein in use the surrounding flange receives the skin of the amputated limb at a distance spaced from the osseointegrated device.

Abstract: A neural control system comprises an input controller arranged to receive neural data regarding neural signals relating to a bodily state of a subject from at least one neural sensor, at least one machine learning means using at least one machine learning model to process the received neural data to determine at least one output signal required to achieve a desired value of the bodily state, and means arranged to send the determined output signal to at least one output device, whereby the neural control system forms a first control loop providing closed loop control of the bodily state.

Abstract: Method(s) and apparatus are provided for interfacing with a nervous system of a subject.

Abstract: A system for obtaining biological data from a subject animal, the system comprising at least one neural transducer embedded internally within the subject animal and arranged for interaction with nerves of the subject animal, at least one sensor arranged for sensing data of a parameter of the subject animal, and an external module mounted externally on the subject animal and connected by a wired connection to at least one of the at least one neural transducer or the at least one sensor. The wired connection comprises a sealed and ported through skin interface device.

Abstract: Method(s) and apparatus are provided for operating and training an autoencoder. The autoencoder outputs a latent vector of an N-dimensional latent space for classifying input data. The latent vector includes a label vector y and a style vector z. The style vector z is regularised during training for effecting time invariance in the set of label vectors y associated with the input data. Method(s) and apparatus are further provided for controlling the optimisation of an autoencoder. The autoencoder outputting a latent vector of an N-dimensional latent space for classifying input data. The latent vector comprising a label vector y and a style vector z. The regularisation of the style vector z is controlled to increase or decrease the time invariance of the label vectors y. An autoencoder configured based on the above-mentioned trained autoencoder that regularised the style vector z for effecting time invariance in the set of label vectors y associated with the input data during classification.

Abstract: Herein described is an osseointegrated interface device for engagement with an amputated limb including the skin comprising: a cap portion engageable with an osseointegrated device; wherein the cap portion comprises a surrounding flange; and wherein in use the surrounding flange receives the skin of the amputated limb at a distance spaced from the osseointegrated device.