Bruxism Detection System With Chin-Mounted Accelerometer Sensor

• US 20170265801A1
• Filed: 03/15/2017
• Published: 09/21/2017
• Est. Priority Date: 03/15/2016
• Status: Active Application

• Current Assignee: Aalok Nital Patwa, Manasi Nital Patwa
• Original Assignee: Aalok Nital Patwa, Manasi Nital Patwa
• Inventors: Patwa, Aalok Nital, Patwa, Manasi Nital
• Application Number:
  US15/459,490
• Publication Number:
  US 20170265801A1
• Time in Patent Office: Days
• CPC Class Codes: A61B 2505/07 Home care
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• 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 5/4557 Evaluating bruxism
• CPC Class Codes: A61B 5/6814 Head
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

A bruxism detection system is provided that includes a chin-mounted acceleration sensor for detection of teeth grinding and teeth tapping. The system generally includes an acceleration sensor that is adapted to be removably and externally mounted with respect to an individual'"'"'s chin, a bruxism recording and processing system operable on a local processor, and bruxism analysis software that is operable on the local processor or an adjoint processor (or a combination thereof). The system is designed to be used in any convenient location, including an individual'"'"'s home, and is generally reusable by multiple people, thus reducing the cost of bruxism diagnosis and bringing a reliable and effective diagnosis tool to the general public.

Claims

1. A bruxism detection system, comprising:

a. a detection module that includes a single accelerometer and a local processor that includes a recording and processing system, the recording and processing system including (i) a sensor interface, (ii) a processor with memory, (iii) non-volatile storage, (iv) a communication interface, and (v) a power source; and

b. an adjoint processor in communication with the recording and processing system of the detection module,

wherein at least one of the local processor and the adjoint processor is programmed to detect bruxism from multi-axis motion data collected by the single accelerometer by calculating motion signature parameters that include one or more of mean, variance and frequency components of motion, and comparing the calculated motion signature parameters with preconfigured motion signature parameters that correspond to bruxism.

2. The bruxism detection system of claim 1, further comprising a mechanism for detachably securing the detection module to a chin of an individual.

3. The bruxism detection system of claim 2, wherein the mechanism is selected from the group consisting of one or more cloth tapes, gauze pads, straps, bandages and combinations thereof.

4. The bruxism detection system of claim 1, wherein the recording and processing system pre-filters motion data captured by the single accelerometer to eliminate data that is not relevant to detection of bruxism.

5. The bruxism detection system of claim 1, wherein the recording and processing system communicates with the adjoint processor in burst transmissions.

6. The bruxism detection system of claim 1, wherein the recording and processing system establishes an electronic handshake with the adjoint processor before communicating motion data captured by the single accelerometer.

7. The bruxism detection system of claim 1, wherein the adjoint processor is a computer.

8. The bruxism detection system of claim 7, wherein the adjoint computer is selected from the group consisting of a smartphone, laptop computer and a desktop computer.

9. The bruxism detection system of claim 1, wherein the adjoint processor is remotely located relative to the detection module and wherein motion data communicated from the recording and processing system is transmitted over a network.

10. The bruxism detection system of claim 1, wherein the local processor is programmed to detect bruxism from multi-axis motion data collected by the single accelerometer by calculating motion signature parameters that include one or more of mean, variance and frequency components of motion, and comparing the calculated motion signature parameters with preconfigured motion signature parameters that correspond to bruxism.

11. The bruxism detection system of claim 1, wherein the adjoint processor is programmed to detect bruxism from multi-axis motion data collected by the single accelerometer by calculating motion signature parameters that include one or more of mean, variance and frequency components of motion, and comparing the calculated motion signature parameters with preconfigured motion signature parameters that correspond to bruxism.

12. The bruxism detection system of claim 1, both the local processor and the adjoint processor are programmed to detect bruxism from multi-axis motion data collected by the single accelerometer by calculating motion signature parameters that include one or more of mean, variance and frequency components of motion, and comparing the calculated motion signature parameters with preconfigured motion signature parameters that correspond to bruxism.

13. A method for detecting bruxism, comprising:

a. detachably mounting a detection module with respect to a chin of an individual, the detection module including a single accelerometer and a local processor that includes a recording and processing system, wherein the recording and processing system includes (i) a sensor interface, (ii) a processor with memory, (iii) non-volatile storage, (iv) a communication interface, and (v) a power source;

b. collecting multi-axis motion data with the accelerometer included in the detection module;

c. pre-filtering the multi-axis motion data to exclude data that is not relevant to bruxism detection; and

d. transmitting the filtered motion data to an adjoint processor; and

e. processing the filtered motion data at the local processor, the adjoint processor or a combination of the local processor and the adjoint processor to detect bruxism, the processing including calculation of motion signature parameters that include one or more of mean, variance and frequency components of motion, and comparison of the calculated motion signature parameters with preconfigured motion signature parameters that correspond to bruxism.