# US 10,119,807 B2 · Thermal sensor position detecting device

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- Number: US 10,119,807 B2
- Document ID: US10119807B2
- Status: Granted
- Kind: B2
- Application number: 15/816,706
- Filed: 2017-11-17
- Published: 2018-05-24
- Granted: 2018-11-06
- Earliest claimed: 2016-11-18
- Assignees: Child Mind Institute, Inc.
- Applicants: Child Mind Institute, Inc.
- Inventors: Curtis P. White
- Web page: https://patentgrep.com/patent/US10119807B2

## CPC

- G01B 11/14: for measuring distance or clearance between spaced objects or spaced apertures (G01B11/26 takes precedence; rangefinders G01C3/00)
- A61B 5/1114: {Tracking parts of the body}
- A61B 5/16: Devices for psychotechnics (using teaching or educational appliances G09B1/00 - G09B7/00); Testing reaction times {; Devices for evaluating the psychological state}
- A61B 5/6802: {Sensor mounted on worn items}
- A61B 5/7264: {Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems}
- G01B 11/002: {for measuring two or more coordinates}
- G01B 11/26: for measuring angles or tapers; for testing the alignment of axes
- G01V 8/10: Detecting, e.g. by using light barriers (by reflection from the object G01S17/00)
- G06F 3/012: {Head tracking input arrangements}
- G06F 3/014: {Hand-worn input/output arrangements, e.g. data gloves}
- G06F 3/017: {Gesture based interaction, e.g. based on a set of recognized hand gestures (interaction based on gestures traced on a digitiser G06F3/04883)}
- A61B 5/024: Measuring pulse rate or heart rate
- A61B 5/02405: {Determining heart rate variability}
- A61B 5/14551: {for measuring blood gases}
- A61B 5/165: {Evaluating the state of mind, e.g. depression, anxiety}
- A61B 5/486: {Biofeedback (using electroencephalography [EEG] A61B5/375)}
- A61B 5/681: {Wristwatch-type devices}
- A61B 5/7267: {involving training the classification device}
- G06F 3/011: {Arrangements for interaction with the human body, e.g. for user immersion in virtual reality (blind teaching G09B21/00)}
- G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems
- G01B: MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- G01V: GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS (means for indicating the location of accidentally buried, e.g. snow-buried, persons A63B29/02)
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

Devices and methods for determining the position of a device relative to a person using the device, or the position of a part of a user's body relative to the user. One or more thermal sensor may be used to determine the relative position of the device or part of the user's body.

## Claims

### Claim 1

A device capable of collecting data used to determine an angular position of the device relative to a user of the device, comprising:
a first sensor configured to detect temperature at a surface of the user's body;
a non-transitory computer memory;
one or more processors coupled to the memory;
computer software stored in the memory and executable by the one or more processors, said computer software comprising instructions for:
receiving from the first sensor first data corresponding to a first temperature detected when the first sensor is pointed toward the user's body;
receiving from the first sensor second data corresponding to a second temperature detected when the first sensor is not pointed toward the user's body;
combining said first data and said second data to produce a combined data set;
generating a neural network weight from the combined data set using a machine learning algorithm;
generating a neural network function using the neural network weight, wherein the neural network function is configured to receive as input data corresponding to temperature and output a probability of whether the input data matches the first data;
receiving from the first sensor third data corresponding to a third temperature;
inputting the third data to the neural network function to generate a value indicating the extent to which the third data matches the first data.

### Claim 2 (depends on 1)

The device of claim 1 wherein the first sensor is a pyrometer.

### Claim 3 (depends on 1)

The device of claim 1 wherein the first sensor is a proximity sensor further configured to emit light having a predetermined wavelength between 100 nanometers and 1000 nanometers.

### Claim 4 (depends on 3)

The device of claim 3 wherein the first sensor emits infrared radiation.

### Claim 5 (depends on 2)

The device of claim 2 wherein the device is configured to communicate wirelessly with a second device.

### Claim 6 (depends on 1)

The device of claim 1 further comprising a second sensor configured to detect a physiological characteristic of the user.

### Claim 7 (depends on 1)

The device of claim 1 further comprising a second sensor configured to detect temperature at the surface of the user's body, wherein the second sensor is positioned to face in a direction that is not parallel to the first sensor.

### Claim 8 (depends on 7)

The device of claim 7 wherein the second sensor is a pyrometer.

### Claim 9 (depends on 7)

The device of claim 7 wherein the first sensor is a proximity sensor further capable of emitting light having a predetermined wavelength between 100 nanometers and 1000 nanometers.

### Claim 10 (depends on 9)

The device of claim 9 wherein the first sensor emits infrared radiation.

### Claim 11

A method for determining an angular position of a first device relative to a user of the first device, said first device having one or more sensors configured to sense temperature at the surface of the user's body, comprising:
receiving from a first sensor first data corresponding to a first temperature detected when the first sensor is pointed toward a part of the user;
receiving from the first sensor second data corresponding to a second temperature detected when the first sensor is not pointed toward said part of the user;
producing a combined data set by combining said first data and said second data;
generating a neural network weight from the combined data set using a machine learning algorithm;
generating a neural network function using the neural network weight, wherein the neural network function is configured to receive as input data corresponding to temperature and output a probability of whether the input data matches the first data;
receiving from the first sensor third data corresponding to a third temperature;
inputting the third data to the neural network function to generate a value indicating the extent to which the third data matches the first data.

### Claim 12 (depends on 11)

The method of claim 11 further comprising:
receiving from a second sensor third data corresponding to a third temperature detected when the second sensor is pointed toward a part of the user;
receiving from the second sensor fourth data corresponding to a fourth temperature detected when the second sensor is not directed toward said part of the user;
wherein said combined data set is produced by combining said first data, said second data, said third data, and said fourth data.

### Claim 13 (depends on 12)

The method of claim 12 wherein said second sensor is positioned to face in a direction that is not parallel to the first sensor.

### Claim 14 (depends on 12)

The method of claim 12 wherein said third temperature is the same as said first temperature.

### Claim 15 (depends on 12)

The method of claim 12 wherein said fourth temperature is the same as said second temperature.

### Claim 16 (depends on 12)

The method of claim 12 wherein data concerning the angular position of the first device relative to the user of the first device and data concerning the relational position of the device relative to the user's body are wirelessly communicated to a second device.

### Claim 17 (depends on 12)

The method of claim 12 further comprising:
receiving from a third sensor fifth data corresponding to a fifth temperature detected when the third sensor is pointed toward a part of the user;
receiving from the third sensor sixth data corresponding to a sixth temperature detected when the third sensor is not directed toward said part of the user;
wherein said combined data set is produced by combining said first data, said second data, said third data, said fourth data, said fifth data, and said sixth data.

### Claim 18 (depends on 17)

The method of claim 17 wherein said second sensor is positioned to face in a direction that is not parallel to the first sensor.

### Claim 19 (depends on 18)

The method of claim 18 wherein said third sensor is positioned to face in a direction that is not parallel to the first sensor and not parallel to the second sensor.

### Claim 20 (depends on 19)

The method of claim 19 wherein data concerning the angular position of the first device relative to the user of the first device and data concerning the relational position of the device relative to the user's body are wirelessly communicated to a second device.