Patent ID: 11911147
Assignee: BERTEC CORPORATION
Field: Medical technology (Instruments)
Classification: CPC A | IPC A

Claim 10:
11. A body sway measurement system, comprising:
an inertial measurement unit or camera configured to generate time series output data for determining one or more parameters indicative of the body sway of a user; and
a computing device including a data processor, the data processor including at least one hardware component, the data processor being operatively coupled to the inertial measurement unit or camera, the data processor configured to receive the time series output data from the inertial measurement unit or camera, and the data processor and/or a cloud server configured to determine the one or more parameters indicative of the body sway of the user using a neural network;
wherein the data processor and/or the cloud server is configured to determine the one or more parameters indicative of the body sway of the user by performing the following steps:
collecting, during training of the neural network, a plurality of time series training datasets that correspond to respective ones of a plurality of different determinate classes, the plurality of time series training datasets comprising a time series raw inertial measurement unit output dataset, the plurality of different determinate classes corresponding to respective numerical values on a sway stability scale, the sway stability scale comprising a first end value, a second end value, and a plurality of intermediate values between the first end value and the second end value, the first end value on the sway stability scale being indicative of poor body stability, the second end value on the sway stability scale being indicative of excellent body stability, and the plurality of intermediate values being indicative of body stability classifications between poor and excellent body stability;
associating, during training of the neural network, each of the plurality of the time series training datasets with a particular one of the plurality of different determinate classes, wherein associating each of the plurality of the time series training datasets with a particular one of the plurality of different determinate classes includes pairing the time series raw inertial measurement unit output dataset, with a particular one of the plurality of different determinate classes;
inputting, during inference, the time series output data from the inertial measurement unit or camera into the neural network that has previously undergone training; and
utilizing the trained neural network to associate the time series output data with one of the plurality of different determinate classes so as to generate the one or more parameters indicative of the body sway of the user.