Calculate Physiological State and Control Smart Environments via Wearable Sensing Elements

Patent metadata

Field	Value
Publication number	US-2019175016-A1
Application number	US-201816218612-A
Country	US
Kind code	A1
Filing date	Dec 13, 2018
Priority date	Dec 11, 2017
Publication date	Jun 13, 2019
Grant date	—

Abstract

An approach is disclosed that receives, at a wearable sensing element worn by a user, sensor data that pertains to the user's physiological functions. Physiological states pertaining to the user are calculated from the received sensor data, with the physiological states including both physical states and mental states. The calculated physiological state is matched to an environmental action states, and environmental actions are responsively performed to change a physical environment of the user.

First claim

What is claimed is:

1 . A method, implemented by an information handling system comprising a processor and a memory accessible by the processor, the method comprising:
receiving, at a wearable sensing element worn by a user, a set of sensor data corresponding to a current set of user physiological functions pertaining to the user; calculating, from the received set of sensor data, a plurality of physiological states pertaining to the user, wherein at least one of the physiological states is a physical state and wherein at least one of the physiological states is a mental state; matching the calculated physiological states to a plurality of environmental action states; and performing one or more environmental actions to change a physical environment of the user, wherein the performed environmental actions correspond to one or more of the plurality of environmental states that matched the calculated physiological states.

2 . The method of claim 1 further comprising:
training a neural network model with a plurality of collections of sensor data received at the wearable sensing element over a period of time, the method further comprising:
inputting the received sensor data to the trained neural network model; and
receiving, from the trained neural network model, the calculated plurality of physiological states.

3 . The method of claim 1 wherein at least one of the performed environmental actions is selected from the group consisting of a change to an ambient light level of the physical environment, a change to a temperature of the physical environment, a change to a sound level of a sound system in the physical environment, a change to a fan speed level of a fan in the physical environment, and a change to a humidity level of the physical environment.

4 . The method of claim 1 further comprising:
transmitting the received set of sensor data to a second device, wherein the second device performs the environmental actions.

5 . The method of claim 1 further comprising:
prior to the performance of the environmental actions:
configuring a plurality of environmental actions that include the one or more environmental actions, wherein the configuring includes associating each of the configured environmental actions with one or more environmental states, wherein the environmental states are included in the plurality of physiological states; and
storing the configured environmental actions in a data store, wherein the matching retrieves the environmental states from the data store and results in the configured environmental actions that match the user's calculated physiological states.

6 . The method of claim 1 wherein at least one of the mental states is selected from the group consisting of a depressed mental state, a sad mental state, a happy mental state, and a content mental state.

7 . The method of claim 1 wherein at least one of the physical states is selected from the group consisting of a tired physical state, an energetic physical state, and an asleep physical state.

8 . A wearable information handling system comprising:
one or more processors; a memory coupled to at least one of the processors; and a set of instructions stored in the memory and executed by at least one of the processors to:
receiving, at a wearable sensing element worn by a user, a set of sensor data corresponding to a current set of user physiological functions pertaining to the user;
calculating, from the received set of sensor data, a plurality of physiological states pertaining to the user, wherein at least one of the physiological states is a physical state and wherein at least one of the physiological states is a mental state;
matching the calculated physiological states to a plurality of environmental action states; and
performing one or more environmental actions to change a physical environment of the user, wherein the performed environmental actions correspond to one or more of the plurality of environmental states that matched the calculated physiological states.

9 . The information handling system of claim 8 wherein the actions further comprise:
training a neural network model with a plurality of collections of sensor data received at the wearable sensing element over a period of time, the
inputting the received sensor data to the trained neural network model; and
receiving, from the trained neural network model, the calculated plurality of physiological states.

10 . The information handling system of claim 8 wherein at least one of the performed environmental actions is selected from the group consisting of a change to an ambient light level of the physical environment, a change to a temperature of the physical environment, a change to a sound level of a sound system in the physical environment, a change to a fan speed level of a fan in the physical environment, and a change to a humidity level of the physical environment.

11 . The information handling system of claim 8 wherein the actions further comprise:
transmitting the received set of sensor data to a second device, wherein the second device performs the environmental actions.

12 . The information handling system of claim 8 wherein the actions further comprise:
prior to the performance of the environmental actions:
configuring a plurality of environmental actions that include the one or more environmental actions, wherein the configuring includes associating each of the configured environmental actions with one or more environmental states, wherein the environmental states are included in the plurality of physiological states; and
storing the configured environmental actions in a data store, data store and results in the configured environmental actions that match the user's calculated physiological states.

13 . The information handling system of claim 8 wherein at least one of the mental states is selected from the group consisting of a depressed mental state, a sad mental state, a happy mental state, and a content mental state.

14 . The information handling system of claim 8 wherein at least one of the physical states is selected from the group consisting of a tired physical state, an energetic physical state, and an asleep physical state.

15 . A computer program product comprising:
a computer readable storage medium comprising a set of computer instructions, the computer instructions effective to: receiving, at a wearable sensing element worn by a user, a set of sensor data corresponding to a current set of user physiological functions pertaining to the user; calculating, from the received set of sensor data, a plurality of physiological states pertaining to the user, wherein at least one of the physiological states is a physical state and wherein at least one of the physiological states is a mental state; matching the calculated physiological states to a plurality of environmental action states; and performing one or more environmental actions to change a physical environment of the user, wherein the performed environmental actions correspond to one or more of the plurality of environmental states that matched the calculated physiological states.

16 . The computer program product of claim 15 wherein the actions further comprise:
training a neural network model with a plurality of collections of sensor data received at the wearable sensing element over a period of time, the computer program product wherein the actions further comprise:
inputting the received sensor data to the trained neural network model; and
receiving, from the trained neural network model, the calculated

Assignees

• IBM

Inventors

• Coden Anni R
• Jamjoom Hani T
• Lubensky David M
• Manweiler Justin Gregory
• Vogt Katherine
• Weisz Justin

Classifications

• A61B5/1107

  Measuring contraction of parts of the body, e.g. organ or muscle · CPC title

• G08B21/0453

  worn on the body to detect health condition by physiological monitoring, e.g. electrocardiogram, temperature, breathing (detecting, measuring or recording for diagnostic purposes A61B5/00) · CPC title

• G06F1/163

  Wearable computers, e.g. on a belt · CPC title

• A61B5/7282

  Event detection, e.g. detecting unique waveforms indicative of a medical condition (cough events A61B5/0823; seizures A61B5/4094; sleep apnoea A61B5/4818) · CPC title

• G16H40/67

  for remote operation · CPC title