公开(公告)号：US20220172023A1

公开(公告)日：2022-06-02

申请号：US17599148

申请日：2019-03-29

Applicant: AGENCY FOR SCIENCE, TECHNOLOGY AND RESEARCH

Inventor： Haihong ZHANG ,  Huijuan YANG ,  Zhuo ZHANG ,  Chuan Chu WANG ,  Dajiang HE ,  Kai Keng ANG

IPC: G06N3/04 ,  G06N3/12

Abstract: Disclosed is a system and method for measuring a non-stationary brain signal. Per the method, the system receives brain signals, extracts one or more features from the brain signals, determines, based on the Receive brain signals extracted one or more features, a super feature set describing dynamic behaviour of the brain signals, and forms a cluster-recurrent-neural-network (CRNN) from one or more samples taken from the super feature set, by formExtract one or more features ing at least one cluster of the one or more samples based on the one or more from the brain signals features, to estimate a brain state of interest in each cluster of brain signals; using a Monte Carlo approach to estimate an a posteriori probability density function of the brain state of interest by applying the CRNN to each cluster of the at least one cluster; and determining the brain state of interest from the estimated density function.

公开(公告)号：US20220164029A1

公开(公告)日：2022-05-26

申请号：US17599099

申请日：2019-03-29

Applicant: AGENCY FOR SCIENCE, TECHNOLOGY AND RESEARCH

Inventor： Zheng Yang CHIN ,  Kai Keng ANG

IPC: G06F3/01 ,  G06K9/62 ,  G06N20/00

Abstract: Disclosed is a method for classifying signals for movement control of an autonomous vehicle. The method includes receiving first data comprising concurrently recorded electroencephalogram (EEG) and electromyogram (EMG) signals from a user. The data is used to train a classification model based on the recorded signals. The method further involves receiving second data comprising further EEG and EMG signals recorded from the user, comparing the second data to the classification model to determine a user movement represented by the second data, and determining a control signal for controlling the autonomous vehicle, based on the user movement. This may be used in a further method for identifying an event.

公开(公告)号：US20210076963A1

公开(公告)日：2021-03-18

申请号：US17050284

申请日：2019-04-29

Applicant: AGENCY FOR SCIENCE, TECHNOLOGY, AND RESEARCH

Inventor： Huijuan YANG ,  Cuntai GUAN ,  Haihong ZHANG ,  Kai Keng ANG ,  Rosa Qi Yue SO

IPC: A61B5/04 ,  G08C17/02 ,  A61B5/0476 ,  A61B5/00 ,  G06N3/08 ,  G06N20/10 ,  G16H20/30 ,  G16H20/40

Abstract: Disclosed is a signal processing system for a brain machine interface (BMI) and a method performed by such a signal processing system. The method involves receiving and filtering input data comprising cortical signal samples, calculating a threshold for detection of spikes, identifying spikes in subsequently received samples, and outputting spike data corresponding to the identified spike or spikes.

公开(公告)号：US20170181915A1

公开(公告)日：2017-06-29

申请号：US15328010

申请日：2015-07-23

Applicant: AGENCY FOR SCIENCE, TECHNOLOGY AND RESEARCH

Inventor： Kai Keng ANG ,  Cuntai GUAN ,  Kok Soon PHUA ,  Longjiang ZHOU ,  Chuan Chu WANG

IPC: A61H1/02 ,  A61B5/22 ,  A61B5/0476 ,  G09B5/06 ,  A61B5/11

CPC classification number: A61H1/0274 ,  A61B5/0476 ,  A61B5/0482 ,  A61B5/1121 ,  A61B5/1126 ,  A61B5/225 ,  A61B5/7475 ,  A61B2560/0223 ,  A61H1/02 ,  A61H1/0285 ,  A61H1/0288 ,  A61H2001/0203 ,  A61H2201/1635 ,  A61H2201/1671 ,  A61H2201/5043 ,  A61H2201/5048 ,  A61H2201/5061 ,  A61H2201/5064 ,  A61H2230/105 ,  G06F3/014 ,  G06F3/015 ,  G06F3/016 ,  G09B5/06

Abstract: A method for calibrating and executing a rehabilitation exercise for a stroke-affected limb of a stroke patient is disclosed, the method comprising the steps of providing a haptic device for an able limb of the stroke patient to manipulate to perform a calibration action to result in a first position of the haptic device, and providing the haptic device for the stroke-affected limb to manipulate to perform the calibration action to result in a second position of the haptic device. The method further comprises the steps of moving the haptic device coupled with the stroke-affected limb from the second position towards the first position until a predetermined counterforce is detected, indicating an extreme position for the stroke-affected limb using the haptic device, and calibrating the haptic device with the extreme position such that during the rehabilitation exercise, the haptic device is prevented from moving beyond the extreme position.