公开(公告)号：US20210362005A1

公开(公告)日：2021-11-25

申请号：US16963385

申请日：2019-01-16

Applicant: NEC Corporation

Inventor： Yuki KOSAKA ,  Yusuke TAKAHASHI ,  Charles CHOY

IPC: A63B24/00 ,  G06K9/62

Abstract: The present disclosure relates to method and system for signal processing rehabilitation exercise signals. The method comprises the step of receiving a first and a second motion signals associated with movements of a body part, wherein the motion signals comprise temporal data of the movements. The method further comprises the step of segmenting each of the first and second motion signals into a plurality of segmented signals based on gradients of the motion signals, wherein each segmented signal has consistent gradient. The method further comprises the step of automatically modifying the segmented signals to form multiple combinations of matching signals with similar gradients between the first and second motion signals, such that the first and second motion signals are in one-to-one correspondence. The method further comprises the step of extracting corresponding time intervals of the matching signals in the correspondences.

公开(公告)号：US20210319867A1

公开(公告)日：2021-10-14

申请号：US17271921

申请日：2019-08-23

Applicant: NEC Corporation

Inventor： Ni Ni SOE ,  Charles CHOY

IPC: G16H10/60 ,  G16H15/00 ,  G16H50/20 ,  G16H40/63

Abstract: Systems and methods predict functional and cognitive recovery of a person after the person has experienced a brain injury such as traumatic brain injury, cerebrovascular disease, and stroke. A computer system includes a database that stores multimodal data of the person recovering from a brain injury and a computer that analyzes the multimodal data over multiple intervals that span several months of time. The computer executes longitudinal heterogeneous trajectory analysis on the multimodal data and executes separation of heterogeneous groups that include good recovery potential of the brain injury, moderate recovery potential of the brain injury, and poor recovery potential of the brain injury. Based on the longitudinal heterogeneous trajectory analysis and the separation of the heterogeneous groups, the computer predicts functional recovery of the person from the brain injury.