Wearable device and data transmission method

• US 10,281,953 B2
• Filed: 12/27/2017
• Issued: 05/07/2019
• Est. Priority Date: 11/29/2013
• Status: Active Grant

• Current Assignee: Ouraring, Inc. (Oura Health Oy)
• Original Assignee: Motiv Inc.
• Inventors: von Badinski, Curt C., Twiss, Peter Miles, Post, Daniel Jeffrey, Ambuehl, Anthony, Strasser, Michael J., Strasser, Eric
• Primary Examiner(s): Hunnings, Travis R
• Application Number:
  US15/854,783
• Publication Number:
  US 20180120892A1
• Time in Patent Office: 496 Days
• CPC Class Codes: A61B 2560/0214 of power generation or supply
• CPC Class Codes: A61B 2560/0412 Low-profile patch shaped housings
• 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 2562/0223 Magnetic field sensors
• CPC Class Codes: A61B 2562/0257 Proximity sensors
• CPC Class Codes: A61B 2562/04 Arrangements of multiple sensors of the same type
• CPC Class Codes: A61B 2562/146 for optical coupling
• CPC Class Codes: A61B 2562/164 the sensor is mounted in or on a conformable substrate or carrier
• CPC Class Codes: A61B 2562/166 the sensor is mounted on a specially adapted printed circuit board
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• 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 5/1118 Determining activity level
• CPC Class Codes: A61B 5/1123 Discriminating type of movement, e.g. walking or running A61B5/1116, A61B5/112 take precedence
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/4809 Sleep detection, i.e. determining whether a subject is asleep or not
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/6806 Gloves
• CPC Class Codes: A61B 5/681 : Wristwatch-type devices
• CPC Class Codes: A61B 5/6826 : Finger
• CPC Class Codes: A61B 5/7264 : Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• 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: G01P 15/00 : Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
• CPC Class Codes: G04G 21/02 : Detectors of external physical values, e.g. temperature
• CPC Class Codes: G06F 1/1626 : with a single-body enclosure integrating a flat display, e.g. Personal Digital Assistants [PDAs]
• CPC Class Codes: G06F 1/163 : Wearable computers, e.g. on a belt
• CPC Class Codes: G06F 1/1632 : External expansion units, e.g. docking stations
• CPC Class Codes: G06F 1/1635 : Details related to the integration of battery packs and other power supplies such as fuel cells or integrated AC adapter
• CPC Class Codes: G06F 1/1694 : the I/O peripheral being a single or a set of motion sensors for pointer control or gesture input obtained by sensing movements of the portable computer
• CPC Class Codes: G06F 21/44 : Program or device authentication
• CPC Class Codes: G06F 2200/1633 : Protecting arrangement for the entire housing of the computer
• CPC Class Codes: G06F 2203/0331 : Finger worn pointing device
• CPC Class Codes: G06F 3/014 : Hand-worn input/output arrangements, e.g. data gloves
• CPC Class Codes: 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
• CPC Class Codes: G06F 3/0346 : with detection of the device orientation or free movement in a 3D space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors
• CPC Class Codes: G06F 3/14 : Digital output to display device ; Cooperation and interconnection of the display device with other functional units
• CPC Class Codes: G06F 3/1423 : controlling a plurality of local displays, e.g. CRT and flat panel display
• CPC Class Codes: G06F 3/1454 : involving copying of the display data of a local workstation or window to a remote workstation or window so that an actual copy of the data is displayed simultaneously on two or more displays, e.g. teledisplay
• CPC Class Codes: G06F 3/147 : using display panels
• CPC Class Codes: G06V 40/10 : Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
• CPC Class Codes: G06V 40/28 : Recognition of hand or arm movements, e.g. recognition of deaf sign language static hand signs G06V40/113
• CPC Class Codes: G08B 21/02 : Alarms for ensuring the safety of persons
• CPC Class Codes: G08B 5/36 : using visible light sources
• CPC Class Codes: G08C 17/02 : using a radio link
• CPC Class Codes: G09G 2370/16 : Use of wireless transmission of display information
• CPC Class Codes: G09G 2380/02 : Flexible displays
• CPC Class Codes: G16H 40/67 : for remote operation
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 80/00 : ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
• CPC Class Codes: H02J 2310/23 : The load being a medical device, a medical implant, or a life supporting device
• CPC Class Codes: H02J 7/0042 : characterised by the mechanical construction
• CPC Class Codes: H02J 7/0044 : specially adapted for holding portable devices containing batteries H02J7/0045 takes precedence

Abstract

The disclosure discloses a wearable computing device (WCD) that would selectively and automatically activate a transceiver of the WCD for data transmission based on sensor data obtained from a sensor module of the WCD. In some example, the sensor module may convert the physical movements of the WCD into sensor data. Then, a processor module of the WCD compares the sensor data to a predetermined pattern pre-stored in the memory. If the sensor data matches the predetermined pattern, the processor module activates the transceiver to receive/transmit data packets. If the sensor data does not match the predetermined pattern, the process goes back to the beginning, where the processor module monitors the movement of the WCD through the sensors.

Claims

1. A wearable computing device, configured as a ring for being worn around the finger of a user, the wearable computing device comprising:

an interior enclosure portion for enclosing a printed circuit board, the printed circuit board including a plurality of components of the wearable computing device;

an exterior enclosure structure for receiving the printed circuit board and for being coupled with the interior enclosure portion to form a housing of the wearable computing device;

a curved, rechargeable battery, disposed proximate the exterior enclosure, the rechargeable battery configured for being wirelessly charged;

a flexible printed circuit board disposed proximate the curved battery, the flexible printed circuit board comprising;

a plurality of components, the plurality of components disposed on the flexible printed circuit board, the plurality of components comprising an electromagnetic induction or RF charging mechanism, a microprocessor, a sensor module, a light emitting diode, and a transciever;

wherein at least one of the interior enclosure portion and the exterior enclosure structure defines one or more windows that facilitates at least one of data acquisition, data transmission, electromagnetic radiation aquistion, and electromagnetic transmission.

2. The wearable computing device of claim 1, wherein the at least one component comprises:

at least one processor;

at least one sensor configured to measure a sensor data; and

at least one transciever,

wherein the at least one processor activates the at least one transceiver to transmit a first data packet and/or receive a second data packet based in part on the sensor data.

3. The wearable computing device of claim 2, wherein the sensor comprises an accelerometer, and the sensor data comprises an acceleration measurement of an accelerometer disposed on the flexible printed circuit board of the wearable computing device.

4. The wearable computing device of claim 3, wherein the sensor data further comprises an axial rotation measurement.

5. The wearable computing device of claim 1, wherein the sensor comprises a capacitor, and the sensor data further comprises a capacitive touch and/or the measurement of one or more gesture inputs.

6. The wearable computing device of claim 3, wherein the sensor comprises one or more of a light sensor, a gyroscope, and a magnetometer, and the sensor data further comprises one or more of a measurement from a light sensor, a gyroscope and/or a magnetometer.

7. The wearable computing device of claim 6, wherein the sensor data further comprises an orientation measurement based on a received signal strength indicator (RSSI) signal.

8. The wearable computing device of claim 3, wherein the acceleration measurement comprises at least one direction vector, wherein if a polarity of the at least one direction vector changes, the at least one processor updates a transition count and activates the at least one transceiver to transmit the first data packet and/or receive the second data packet if the transition count is greater than a predetermined threshold.

9. The wearable computing device of claim 8, wherein the activation of the at least one transceiver is based at least in part on a transition of the activity of the wearer and/or an input from the wearer.

10. The wearable computing device of claim 9, wherein the sensor data comprises a series of samples is obtained based on a vibration generated by an external vibration mechanism.

11. The wearable computing device of claim 2, wherein the at least one processor determines an activity of a wearer based at least in part on the sensor data and activates the least one transceiver to transmit a first data packet and/or receive a second data packet based at least in part on the activity of the wearer.

12. The wearable computing device of claim 2, wherein the at least one processor processes the sensor data to obtain a series of samples, compare the series of samples to a predetermined pattern, and activate the at least one transceiver to transmit the first data packet and/or receive the second data packet if the series of samples matches the predetermined pattern.

13. The wearable computing device of claim 12, wherein the comparison between the series of samples and the predetermined pattern is determined by a recognition technique.

14. The wearable computing device of claim 1, wherein the interior enclosure portion comprises potting.

15. The wearable computing device of claim 14, wherein the potting is transparent.

16. A method, adapted to a wearable computing device in the form factor of a ring for being worn around the finger of a user, the wearable computing device comprising at least one sensor module having at least one sensor, at least one processor, and at least one transceiver;

the method comprising;

obtaining, by the sensor of the sensor module, sensor data indicating a motion of the finger or a hand adjoined to the finger wearing the wearable computing device;

comparing, by one of the at least one processors, the obtained sensor data to a predetermined pattern of motion;

determining, by one of the at least one processors, whether the obtained sensor data matches a predetermined pattern;

determining, by one of the at least one processors, a characteristic of an activity of the user of the wearable computing device when the obtained sensor data matches the predetermined pattern; and

activating the at least one transceiver to transmit a first data packet and/or receive a second data packet in response to a confirmation of the sensor data matching the predetermined pattern.

17. The method of claim 16, further comprising:

determining that the sensor data matches the predetermined pattern based at least in part on a completion of the activity.

18. The method of claim 16, further comprising:

determining that the sensor data matches the predetermined pattern based at least in part on a start of the activity.

19. The method of claim 16, further comprising:

determining that the sensor data matches the predetermined pattern based at least in part on a transition between different activities.

20. The method of claim 16, wherein the sensor data further comprises an axial rotation measurement.

21. The method of claim 16, wherein the at least one sensor module comprises one or more of a light sensor, a gyroscope, and/or a magnetometer, and the sensor data further comprises a measurement from one or more of the light sensor, a gyroscope, and/or a magnetometer.

22. The method of claim 21, wherein the sensor data further comprises an orientation measurement based on a received signal strength indicator (RSSI) signal.

23. The method of claim 16, further comprising:

converting the sensor data into a series of samples;

comparing the series of samples to the predetermined pattern; and

determining that the sensor data matches the predetermined pattern if the series of samples matches the predetermined pattern.

24. The method of claim 23, wherein the comparing between the series of samples and the predetermined pattern is determined by a recognition technique.

25. The method of claim 24, wherein the recognition technique comprises one or more calculations of coefficients based on a neural network.

26. The method device of claim 25, wherein the recognition technique comprises a frequency domain algorithm.

27. The method of claim 16, wherein the predetermined pattern comprises a predetermined waveform having a sequence of peaks having different amplitudes.

28. The method of claim 16, wherein the predetermined pattern is a predetermined waveform comprising a sequence of peaks different in frequency.

29. The method of claim 21, further comprising:

converting the sensor data into at least one direction vector and;

detecting an orientation change of the wearable computing device based at least in part on a polarity of the at least one direction vector;

comparing the number of detected orientation changes to the predetermined pattern; and

determining that the sensor data matches the predetermined pattern if the number of the detected orientation changes matches the predetermined pattern.

30. A non-transitory computer readable storage medium storing computer readable instructions for implementation by a processor of a wearable computing device, the wearable computing device being in the form factor of a ring for being worn around the finger of a user and including a sensor module having a sensor and a transciever, which instructions, when executed by the processor, causes the processor to perform operations comprising:

obtaining, by the sensor of the sensor module, sensor data indicating a motion of the finger or a hand adjoined to the finger wearing the wearable computing device;

comparing, by the processor, the obtained sensor data to a predetermined pattern;

determining, by the processor, whether the obtained sensor data matches a predetermined pattern;

determining, by the processor, a characteristic of an activity of the user of the wearable computing device when the obtained sensor data matches the pattern; and

activating the at least one transceiver to transmit a first data packet and/or receive a second data packet in response to a confirmation of the sensor data matching the predetermined pattern.

31. The non-transitory computer readable storage medium of claim 30, wherein the processor further executes an operation comprising:

determining that the sensor data matches the predetermined pattern based at least in part on a completion of the activity.

32. The non-transitory computer readable storage medium of claim 30, wherein the processor further executes an operation comprising:

determining that the sensor data matches the predetermined pattern based at least in part on a start of the activity.

33. The non-transitory computer readable storage medium of claim 30, wherein the sensor module comprises one or more of a light sensor, a gyroscope, and/or a magnetometer, and the sensor data further comprises one or more of a measurement from the light sensor, a gyroscope, and/or a magnetometer.

34. The non-transitory computer readable storage medium of claim 30, wherein the processor further executes an operation comprising:

converting the sensor data into a series of samples;

comparing the series of samples to the predetermined pattern; and

determining that the sensor data matches the predetermined pattern if the series of samples matches the predetermined pattern.

35. The non-transitory computer readable storage medium of claim 34, wherein the processor further executes an operation comprising:

comparing between the series of samples and the predetermined pattern is determined by a recognition technique.

36. The non-transitory computer readable storage medium of claim 35, wherein the recognition technique comprises calculation of coefficients based on a neural network.

37. The non-transitory computer readable storage medium of claim 30, wherein the processor further executes operations comprising:

converting the sensor data into at least one direction vector;

detecting a characteristic of an orientation changes of the wearable computing device based at least in part on the at least one direction vector;

comparing the characteristics of the detected orientation changes to the predetermined pattern; and

determining whether the sensor data matches the predetermined pattern.

38. A wearable computing device, configured as a ring for being worn around the finger of a user, the wearable computing device comprising:

an exterior enclosure structure forming a first part of a housing for the wearable computing device, the exterior enclosure structure retaining one or more electronic components, the one or more electronic components comprising;

a curved printed circuit board comprising a microprocessor, the printed circuit board disposed proximate the exterior enclosure structure;

a curved battery disposed proximate the printed circuit board;

one or more sensors disposed within the housing, the one or more sensors for sensing one or more conditions of the user;

a light emitting diode; and

a transparent interior enclosure portion configured for being coupled to the exterior enclosure structure, the interior enclosure portion forming a second part of the housing.

39. The wearable computing device of claim 38, wherein the interior enclosure comprises potting.

40. The wearable computing device of claim 39, wherein the potting comprises an epoxy.

41. The wearable computing device of claim 39, wherein the potting forms a water-resistant seal against the exterior enclosure for encasing the one or more electronic components.

42. The wearable computing device of claim 41, wherein the one or more electronic components further comprises a communications module.

43. The wearable computing device of claim 41, wherein the communications module is configured for synchronizing with a cellular telephone or a watch.