Head-mounted physiological signal monitoring system, devices and methods

• US 10,342,482 B1
• Filed: 01/12/2017
• Issued: 07/09/2019
• Est. Priority Date: 02/18/2014
• Status: Active Grant

• Current Assignee: Orbital Research, Inc.
• Original Assignee: Orbital Research, Inc.
• Inventors: Lisy, Frederick J., Opperman, Anthony, Dashevsky, David D.
• Primary Examiner(s): Benlagsir, Amine
• Application Number:
  US15/404,223
• Time in Patent Office: 908 Days
• CPC Class Codes: A41D 1/002 adapted to accommodate electronic equipment patients' garments for medical monitoring A41D13/1281; luminous ornaments A41D27/085
• CPC Class Codes: A41D 20/00 Wristbands or headbands, e.g. for absorbing sweat
• CPC Class Codes: A42B 1/041 Peakless soft head coverings, e.g. turbans or berets A42B1/045, A42B1/046 take precedence
• CPC Class Codes: A42B 1/12 Bathing caps
• CPC Class Codes: A42B 1/242 Means for mounting detecting, signalling or lighting devices
• CPC Class Codes: A42B 3/0433 Detecting, signalling or lighting devices
• CPC Class Codes: A42B 3/0453 Signalling devices, e.g. auxiliary brake or indicator lights
• CPC Class Codes: A61B 2503/10 Athletes
• CPC Class Codes: A61B 2560/0214 of power generation or supply
• CPC Class Codes: A61B 2560/0219 of externally powered implanted units
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 2560/0247 for compensation or correction of the measured physiological value
• CPC Class Codes: A61B 2560/0468 Built-in electrodes
• CPC Class Codes: A61B 2562/0204 Acoustic sensors
• CPC Class Codes: A61B 2562/0209 Special features of electrodes classified in A61B5/24, A61B5/25, A61B5/283, A61B5/291, A61B5/296, A61B5/053
• CPC Class Codes: A61B 2562/0214 Capacitive electrodes
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 2562/0247 Pressure sensors
• CPC Class Codes: A61B 2562/125 characterised by the manufacture of electrodes
• CPC Class Codes: A61B 3/113 for determining or recording eye movement
• CPC Class Codes: A61B 5/0006 : ECG or EEG signals
• CPC Class Codes: A61B 5/0066 : Optical coherence imaging
• CPC Class Codes: A61B 5/0073 : by tomography, i.e. reconstruction of 3D images from 2D projections A61B5/0066 takes precedence
• CPC Class Codes: A61B 5/01 : Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue clinical contact thermometers G01K13/20
• CPC Class Codes: A61B 5/02055 : Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/02405 : Determining heart rate variability
• CPC Class Codes: A61B 5/02416 : using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/0245 : by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/036 : by means introduced into body tracts A61B5/032 and A61B5/035 take precedence
• CPC Class Codes: A61B 5/0533 : Measuring galvanic skin response
• CPC Class Codes: A61B 5/0816 : Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/11 : Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/1112 : Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/14542 : for measuring blood gases A61B5/14551 takes precedence
• CPC Class Codes: A61B 5/14551 : for measuring blood gases
• CPC Class Codes: A61B 5/16 : Devices for psychotechnics using teaching or educational appliances G09B1/00 - G09B7/00; Testing reaction times ; Devices for evaluating the psychological state
• CPC Class Codes: A61B 5/165 : Evaluating the state of mind, e.g. depression, anxiety
• CPC Class Codes: A61B 5/18 : for vehicle drivers or machine operators
• CPC Class Codes: A61B 5/25 : Bioelectric electrodes therefor
• CPC Class Codes: A61B 5/282 : Holders for multiple electrodes for introduction into the body A61B5/287
• CPC Class Codes: A61B 5/287 : Holders for multiple electrodes, e.g. electrode catheters for electrophysiological study [EPS]
• CPC Class Codes: A61B 5/302 : for capacitive or ionised electrodes, e.g. metal-oxide-semiconductor field-effect transistors [MOSFET]
• CPC Class Codes: A61B 5/316 : Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/332 : Portable devices specially adapted therefor
• CPC Class Codes: A61B 5/339 : Displays specially adapted therefor
• CPC Class Codes: A61B 5/398 : Electrooculography [EOG], e.g. detecting nystagmus; Electroretinography [ERG]
• CPC Class Codes: A61B 5/4803 : Speech analysis specially adapted for diagnostic purposes
• CPC Class Codes: A61B 5/4812 : Detecting sleep stages or cycles
• CPC Class Codes: A61B 5/4866 : Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/6803 : Head-worn items, e.g. helmets, masks, headphones or goggles
• CPC Class Codes: A61B 5/6806 : Gloves
• CPC Class Codes: A61B 5/681 : Wristwatch-type devices
• CPC Class Codes: A61B 5/6814 : Head
• CPC Class Codes: A61B 5/6817 : Ear canal
• CPC Class Codes: A61B 5/7203 : for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/74 : Details of notification to user or communication with user or patient indicating measured values G01D7/00; user input means input or output arrangements for computers G06F3/00
• CPC Class Codes: A61B 5/7405 : using sound
• CPC Class Codes: A61B 5/741 : using synthesised speech
• CPC Class Codes: A61B 5/742 : using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7445 : Display arrangements, e.g. multiple display units
• CPC Class Codes: A61B 5/7455 : characterised by tactile indication, e.g. vibration or electrical stimulation
• CPC Class Codes: A61B 5/746 : Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61B 5/747 : in case of emergency, i.e. alerting emergency services
• CPC Class Codes: A61B 7/00 : Instruments for auscultation

Abstract

Hat, helmet, and other headgear apparatus includes dry electrophysiological electrodes and, optionally, other physiological and/or environmental sensors to measure signals such as ECG from the head of a subject. Methods of use of such apparatus to provide fitness, health, or other measured or derived, estimated, or predicted metrics are also disclosed.

Claims

1. A head-mounted physiological signal monitoring system comprising:

a headgear apparatus comprising a hat, helmet, earpiece or eyeglasses to fit snugly to, and place light pressure on, a head or in an ear of a subject, and a plurality of electrode connectors attached to or integrated into the headgear apparatus;

a plurality of dry electrophysiological electrodes to acquire electrophysiological signals and to be attached to the electrode connectors, each dry electrophysiological electrode of the plurality of dry electrophysiological electrodes comprising a lower surface to contact the subject'"'"'s skin, and a plurality of low aspect ratio protruding surface features on the lower surface; and

at least one electronic component including a processor comprising an algorithm to process the electrophysiological signals,

wherein the processor is to at least in part process the electrophysiological signals to obtain electrocardiogram (ECG) signals.

2. The system of claim 1, wherein the system is to measure basal or resting metabolic rates and/or calories burned or metabolic rate during an activity or time period based on a user input that is measured by or derived from the electrophysiological signals acquired by the plurality of dry electrophysiological electrodes.

3. The system of claim 2, wherein the processor and algorithm are to calculate the basal or resting metabolic rates and/or calories burned or metabolic rate during the activity or time period using statistical analyses coordinated with a database of physical activity data generated from numerous subjects of varying ages, genders, heights, and weights.

4. The system of claim 3, wherein the headgear apparatus further comprises at least one other physiological sensor to acquire a non-electrophysiological signal, and the processor and algorithm are further for deriving at least one other metric based at least in part on the ECG signals and at least in part on the non-electrophysiological signal.

5. The system of claim 4, wherein the at least one other derived metric is selected from the group consisting of stress, preparedness, calories expended, oxygen consumption (VO2), maximal oxygen consumption (VO2 max), carbon dioxide production (VCO2), energy expenditure, and respiratory quotient.

6. The system of claim 5, wherein the at least one other derived metric is reported to the subject and forms a basis of a notice or warning delivered to the subject by an automatic output selected from the group consisting of a visual display, an audible alarm, speech, a mild electrical shock, or an ambient or localized temperature change, or a change in the lighting permitted to enter the eyes of the subject.

7. The system of claim 6, wherein the processor and algorithm are further to calculate the basal or resting metabolic rates and/or calories burned or metabolic rate during the activity or time period based also in part on the non-electrophysiological signal.

8. A head-mounted physiological signal monitoring system comprising:

a headgear apparatus comprising a hat, helmet, earpiece or eyeglasses to fit snugly to, and place light pressure on, a head or in an ear of a subject, a plurality of electrode connectors attached to or integrated into the headgear apparatus, and at least one other physiological sensor to acquire at least one non-electrophysiological signal;

a plurality of dry electrophysiological electrodes to acquire electrophysiological signals and to be attached to the electrode connectors, each dry electrophysiological electrode of the plurality of dry electrophysiological electrodes comprising a lower surface to contact the subject'"'"'s skin, and a plurality of low aspect ratio protruding surface features on the lower surface; and

at least one electronic component including a processor comprising an algorithm to process the electrophysiological signals to obtain electrocardiogram (ECG) signals and to derive at least one physiological metric based at least in part on the ECG signals and at least in part on the at least one non-electrophysiological signal.

9. The system of claim 8, wherein the system is to measure basal or resting metabolic rates and/or calories burned or metabolic rate during an activity or time period based on a user input that is measured by or derived from the electrophysiological signals acquired by the plurality of dry electrophysiological electrodes.

10. The system of claim 9, wherein the processor and algorithm are to calculate the basal or resting metabolic rates and/or calories burned or metabolic rate during the activity or time period using statistical analyses coordinated with a database of physical activity data generated from numerous subjects of varying ages, genders, heights, and weights.

11. The system of claim 10, wherein the at least one derived physiological metric is selected from the group consisting of stress, preparedness, calories expended, oxygen consumption (VO2), maximal oxygen consumption (VO2 max), carbon dioxide production (VCO2), energy expenditure, and respiratory quotient.

12. The system of claim 11, wherein the at least one derived physiological metric is reported to the subject and forms a basis of a notice or warning delivered to the subject by an automatic output selected from the group consisting of a visual display, an audible alarm, speech, a mild electrical shock, or an ambient or localized temperature change, or a change in lighting permitted to enter the eyes of the subject.

13. The system of claim 12, wherein the processor and algorithm are further to calculate the basal or resting metabolic rates and/or calories burned or metabolic rate during the activity or time period based also in part on the non-electrophysiological signal.

14. A head-mounted physiological signal monitoring system comprising:

a headgear apparatus comprising a hat, helmet, earpiece or eyeglasses to fit snugly to, and place light pressure on, a head or in an ear of a subject, and a plurality of electrode connectors attached to or integrated into the headgear apparatus;

a plurality of dry electrophysiological electrodes to acquire electrophysiological signals and to be attached to the electrode connectors, each dry electrophysiological electrode of the plurality of dry electrophysiological electrodes comprising a lower surface to contact the subject'"'"'s skin, and a plurality of low aspect ratio protruding surface features on the lower surface; and

at least one electronic component including a processor comprising an algorithm to process the electrophysiological signals,

wherein the processor and algorithm are to at least in part process the electrophysiological signals to obtain ECG signals.

15. The system of claim 14, wherein the system is to measure basal or resting metabolic rates and/or calories burned or metabolic rate during an activity or time period based on a user input that is measured by or derived from the electrophysiological signals acquired by the plurality of dry electrophysiological electrodes.

16. The system of claim 15, wherein the processor and algorithm are to calculate the basal or resting metabolic rates and/or calories burned or metabolic rate during the activity or time period using statistical analyses coordinated with a database of physical activity data generated from numerous subjects of varying ages, genders, heights, and weights.

17. The system of claim 16, wherein the headgear apparatus further comprises at least one other physiological sensor to acquire a non-electrophysiological signal, and the processor and algorithm are further for deriving at least one other metric based at least in part on the ECG signals and at least in part on the non-electrophysiological signal, the at least one other derived metric selected from the group consisting of stress, preparedness, calories expended, oxygen consumption (VO2), maximal oxygen consumption (VO2 max), carbon dioxide production (VCO2), energy expenditure, and respiratory quotient.

18. The system of claim 17, wherein the at least one other derived metric is reported to the subject and forms a basis of a notice or warning delivered to the subject by an automatic output selected from the group consisting of a visual display, an audible alarm, speech, a mild electrical shock, or an ambient or localized temperature change, or a change in lighting permitted to enter the eyes of the subject.

19. The system of claim 18, wherein the processor and algorithm are further to calculate the basal or resting metabolic rates and/or calories burned or metabolic rate during the activity or time period based also in part on the non-electrophysiological signal.