Michael J Kim

20220350398, Nov 3, 2022

Jul 14, 2022

17/865121

- Brooklyn NY, US
SivaSankara Reddy Bommireddy - Brooklyn NY, US
Michael Dohyun Kim - Sunnyside NY, US
Sean Michael Petterson - Patchogue NY, US

G06F 3/01
G06K 9/62
G06N 20/00

Systems and methods of the present disclosure enable movement recognition and tracking by receiving movement measurements associated with movements of a user. The movement measurements are converted into feature values. An action recognition machine learning model having trained action recognition parameters generates, based on the feature values, an action label representing an action performed during an action-related interval. An activity recognition machine learning model having trained activity recognition parameters generates, based on the action label, an activity label representing an activity performed during an activity-related interval, where the activity includes the action. A task recognition machine learning model having trained task recognition parameters generates, based on the action label and the activity label, a task label representing a task performed during a task-related interval, where the task includes the activity and action. An activity log is updated based on the action label, the activity label, and the task label.

20210290176, Sep 23, 2021

Feb 8, 2021

17/170291

- Brooklyn NY, US
Michael Dohyun Kim - Sunnyside NY, US
Alan Vito Argondizza - New York NY, US
Michael Patrick Spinelli - Croton NY, US

StrongArm Technologies, Inc. - Brooklyn NY

A61B 5/00
G16H 50/30
G16H 40/67
G16H 20/30
A61B 5/11

A system includes a wearable sensor device including an accelerometer configured to be worn by a person and to record sensor data during an activity performed by the person; an analysis element configured to receive the sensor data from the wearable sensor, determine sensor orientation data of the wearable sensor during the activity based on the sensor data, translate the sensor orientation data of the wearable sensor to person orientation data of the person during the activity, determine, for the person during the activity, (a) a lift rate, (b) a maximum sagittal flexion, (c) an average twist velocity, (d) a maximum moment, and (e) a maximum lateral velocity, and determine a score representative of an injury risk to the person during the activity based on such data; and a tangible feedback element configured to provide at least one tangible feedback based on the score so as to reduce the injury risk.

20200113725, Apr 16, 2020

Dec 8, 2016

16/060817

- Brooklyn NY, US
Michael Kim - New York NY, US
Michael Spinelli - New York NY, US
Kyung In Noh - Brooklyn NY, US
Timothy Bromm - Brooklyn NY, US

A61F 5/02

Embodiments of the present disclosure relate to an exoskeleton support system for posture feedback and support during body trunk motions. The system comprises a biomimetic semi-rigid support system connected to body attachment straps for coupling the system onto a user. A feedback pad is positioned on the user's back at a location corresponding to a middle thoracic region of the user. This arrangement causes the user to experience pressure feedback on the back when torso flexion and twisting occur. In addition, progressive resistance on the shoulders is provided via shoulder straps containing stitching in a curved manner to allow for longitudinal flexion and unrestricted arm motion during system use. Further, the system provides indications of safe movements by way of little to no feedback during neutral torso positions. Accordingly, the system only delivers feedback pressure in response to an amount of the user's own body motion.

20190200936, Jul 4, 2019

Nov 13, 2018

16/188864

- Brooklyn NY, US
Michael Dohyun Kim - Sunnyside NY, US
Alan Vito Argondizza - New York NY, US
Michael Patrick Spinelli - Croton NY, US

StrongArm Technologies, Inc. - Brooklyn NY

A61B 5/00
A61B 5/11

A system includes a wearable sensor device including an accelerometer configured to be worn by a person and to record sensor data during an activity performed by the person; an analysis element configured to receive the sensor data from the wearable sensor, determine sensor orientation data of the wearable sensor during the activity based on the sensor data, translate the sensor orientation data of the wearable sensor to person orientation data of the person during the activity, determine, for the person during the activity, (a) a lift rate, (b) a maximum sagittal flexion, (c) an average twist velocity, (d) a maximum moment, and (e) a maximum lateral velocity, and determine a score representative of an injury risk to the person during the activity based on such data; and a tangible feedback element configured to provide at least one tangible feedback based on the score so as to reduce the injury risk.

20170296129, Oct 19, 2017

Apr 13, 2017

15/487410

- Brooklyn NY, US
Michael Dohyun Kim - Sunnyside NY, US
Alan Vito Argondizza - New York NY, US
Michael Patrick Spinelli - Croton NY, US

A61B 5/00
A61B 5/00
A61B 5/00
A61B 5/11
A61B 5/00
A61B 5/00
A61B 5/00
A61B 5/11
A61B 5/00
A61B 5/00

A system includes a wearable sensor configured to be worn by a person and to record sensor data during an activity performed by the person; an analysis element configured to receive the sensor data from the wearable sensor, determine sensor orientation data of the wearable sensor during the activity based on the sensor data, translate the sensor orientation data of the wearable sensor to person orientation data of the person during the activity, determine, for the person during the activity, (a) a lift rate, (b) a maximum sagittal flexion, (c) an average twist velocity, (d) a maximum moment, and (e) a maximum lateral velocity, and determine a score representative of an injury risk to the person during the activity based on such data; and a tangible feedback element configured to provide at least one tangible feedback based on the score so as to reduce the injury risk.