US 2022/0031194 A1Published application

Systems and methods for automated tremor management, tracking and recommendations

AssigneeGyroGear Limited

InventorsJoon Faii Ong, Benjamin T.J. Koh, Youssef Ibrahim, Elliott Baxter, Gordon McCabe, Paul de Panisse Passis, Jon Barrenetxea Carrasco

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Abstract

Systems and methods of the present disclosure include a five-layer environment consisting tremor management hardware, interface, control system, machine learning environment and cloud capabilities. These elements come together to implement program instructions and perform steps to: receive sensory data elements(s) for tremor stat(s), physiological and/or environmental state(s) of the user, user activities and state(s) of the tremor management hardware and based on these state(s) generate at least one actionable tremor mitigation action associated with historical tremor mitigation improvements recorded in a memory, and display at a user computing device the at least one actionable tremor mitigation action to a user, a healthcare provider, or both.

Claims30

Dependent claims

A method comprising:

receiving, by a processor, an accelerometer data signal from a sensor device associated with a user, the accelerometer data signal having a time-varying frequency and a time-varying amplitude of motion detected by the sensor device;
determining, by the processor, a tremor in the accelerometer data signal based at least in part on the time-varying frequency and a tremor frequency range indicative of movement associated with tremors;
determining, by the processor, a tremor frequency and a tremor amplitude of the tremor based on the accelerometer data signal during a period of time associated with the tremor;
generating, by the processor, a mechanical dampening control signal to a tremor management device to cause the device to create a counteracting force or motion resistance or both in response to the tremor frequency and the tremor amplitude;
determining, by the processor, a tremor severity based at least in part on the tremor frequency and the tremor amplitude during the period of time associated with tremor;
storing in a tremor severity history, by the processor, the tremor frequency, the tremor amplitude and the tremor severity during the period of time associated with the tremor;
training, by the processor, a tremor severity pattern recognition model to identify at least one tremor pattern based at least in part on the severity and trained tremor severity model parameters trained according to the tremor severity history;
and
storing, by the processor, the tremor severity pattern recognition model in a tremor severity engine.

6 more elements

A system comprising:

at least a five-layer environment comprising:
i) tremor management device,
ii) a user interface,
iii) a control system,
iv) a machine learning environment, and
v) a cloud environment;
wherein the five-layer environment is configured to implement program instructions to perform steps to:
receive an accelerometer data signal from a sensor device associated with a user, the accelerometer data signal having a time-varying frequency and a time-varying amplitude of motion detected by the sensor device;
determine a tremor in the accelerometer data signal based at least in part on the time-varying frequency and a tremor frequency range indicative of movement associated with tremors;
determine a tremor frequency and a tremor amplitude of the tremor based on the accelerometer data signal during a period of time associated with the tremor;
generate a mechanical dampening control signal to the tremor management device to cause the device to create a counteracting force or motion resistance or both in response to the tremor frequency and the tremor amplitude;
determine a tremor severity based at least in part on the tremor frequency and the tremor amplitude during the period of time associated with tremor;
store in a tremor severity history the tremor frequency, the tremor amplitude and the tremor severity during the period of time associated with the tremor;
train a tremor severity pattern recognition model to identify at least one tremor pattern based at least in part on the severity and trained tremor severity model parameters trained according to the tremor severity history;
and
store the tremor severity pattern recognition model in a tremor severity engine.

13 more elements

A non-transitory computer readable medium having software instructions stored thereon, the software instructions configured to cause at least one processor to perform steps comprising:

receiving an accelerometer data signal from a sensor device associated with a user, the accelerometer data signal having a time-varying frequency and a time-varying amplitude of motion detected by the sensor device;
determining a tremor in the accelerometer data signal based at least in part on the time-varying frequency and a tremor frequency range indicative of movement associated with tremors;
determining a tremor frequency and a tremor amplitude of the tremor based on the accelerometer data signal during a period of time associated with the tremor;
generating a mechanical dampening control signal to a tremor management device to cause the device to create a counteracting force or motion resistance or both in response to the tremor frequency and the tremor amplitude;
determining a tremor severity based at least in part on the tremor frequency and the tremor amplitude during the period of time associated with tremor;
storing in a tremor severity history the tremor frequency, the tremor amplitude and the tremor severity during the period of time associated with the tremor;
training a tremor severity pattern recognition model to identify at least one tremor pattern based at least in part on the severity and trained tremor severity model parameters trained according to the tremor severity history;
and
storing the tremor severity pattern recognition model in a tremor severity engine.

6 more elements

Dependencies are inferred from the claim text.

Facts

Application: 17/393,136Filed 3 Aug 2021
Priority: 3 Aug 2020
Published: 3 Feb 2022
Term ends: Not estimatedThe source records don’t support an estimate.

Classification27 codes

A61B 5/1101
Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb: detecting tremor
A61B 5/0015
Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network: characterised by features of the…
A61B 5/0022
Characterised by features of the telemetry system: monitoring a patient using a global network, e.g. telephone networks, internet
A61B 5/0024
Characterised by features of the telemetry system: for multiple sensor units attached to the patient, e.g. using a body or personal area network

Family

Application63/060,622Us provisional application · filed 3 Aug 2020
Application17/393,136Continuation in part
US 12,295,724 B2Related patent
US 2022/0031194 A1This patent

From the US filing history. Foreign family members aren’t listed.

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