BIO-SENSOR SYSTEM FOR MONITORING TISSUE VIBRATION
A headset comprise a frame and a vibration sensor coupled to the frame. The vibration sensor may be located in a nosepad of the frame, and configured to measure tissue vibrations of a user when the headset of worn by the user. A controller receives a signal corresponding to the measured vibration data from the vibration sensor, and analyzes the received signal to infer a sequence of states of the received signal, such as a sequence of respiratory states. The controller further determines a value of a health metric based upon the inferred sequence of states, e.g., a respiratory rate of the user, and performs an action using the determined value of the health metric.
1 . A headset, comprising:
a frame;
a vibration sensor coupled to the frame, the vibration sensor configured to monitor vibration of a tissue of a user wearing the headset; and
a controller configured to:
receive a signal corresponding to the monitored vibration from the vibration sensor;
analyze the received signal to infer a sequence of states of the received signal;
determine a value of a health metric based upon the inferred sequence of states, and
perform an action using the determined value of the health metric.
2 . The headset of claim 1 , wherein the vibration sensor is located within a nosepad of the frame.
3 . The headset of claim 2 , wherein the nosepad comprises an overmold configured to surround at least a portion of the vibration sensor.
4 . The headset of claim 3 , wherein the overmold contains a slot or cavity configured to accommodate the vibration sensor.
5 . The headset of claim 3 , wherein the vibration sensor is attached to a spring mounted within the overmold or to a flexible portion of the overmold.
6 . The headset of claim 1 , wherein the sequence of states corresponds to respiratory states of the user.
7 . The headset of claim 6 , wherein the controller is further configured to:
use a first model to classify segments of the received signal into two or more classes corresponding to different stages of respiration; and
use a second model to infer the sequence of states based upon the classification results generated by the first model.
8 . The headset of claim 7 , wherein the first model is a kNN model.
9 . The headset of claim 7 , wherein the second model is a hidden semi-Markov model (HSMM).
10 . The headset of claim 6 , where the controller is further configured to:
determine a respiratory rate of the user based upon the sequence of states; and
determine the health metric based upon at least in part upon the respiratory rate, wherein the health metric indicates a physical or emotional condition of the user.
11 . The headset of claim 1 , wherein the controller is further configured to:
monitor the received signal to detect a predetermined characteristic within the received signal;
responsive to detecting the predetermined characteristic:
identify a portion of the vibration signal corresponding to an event associated with the predetermined characteristic;
analyze the identified portion of the vibration signal to classify the identified event; and
perform an action based upon a type of the identified event.
12 . The headset of claim 11 , wherein the controller monitors the received signal to detect the predetermined characteristic in parallel with analyzing the received signal to infer a sequence of states of the received signal.
13 . The headset of claim 11 , wherein the event corresponds to an eating or drinking action by the user.
14 . The headset of claim 13 , wherein performing the action comprises notifying the user of a level of food or fluid consumption of the user, or of a food type consumed by the user.
15 . The headset of claim 13 , wherein the controller is further configured to monitor identified events over time to determine a habit of the user.
16 . The headset of claim 11 , wherein the controller is further configured to cross-reference the a value of the health metric determined based upon the inferred sequence of states with data associated with the identified event to determine a physical or emotional condition of the user.
17 . The headset of claim 1 , wherein the controller is further configured to determine, using the received signal, a tidal volume or respiratory flow rate of the user.
18 . A computer-implemented method, comprising:
receiving, from a vibration sensor coupled to a frame of a headset, signal corresponding to a monitored vibration of a tissue of a user wearing the headset;
analyzing the received signal to infer a sequence of states of the received signal;
determining a value of a health metric based upon the inferred sequence of states, and
performing an action using the determined value of the health metric.
19 . The computer-implemented method of claim 19 , wherein the sequence of states corresponds to respiratory states of the user.
20 . The computer-implemented method of claim 19 , wherein analyzing the received signal to infer a sequence of states of the received signal comprises:
using a first model, classifying segments of the received signal into two or more classes corresponding to different stages of respiration; and
using a second model, inferring the sequence of states based upon the classification results generated by the first model.
21 . The computer-implemented method of claim 19 , wherein the first model is a kNN model, and the second model is a hidden semi-Markov model (HSMM).
22 . The computer-implemented method of claim 18 , further comprising:
monitoring the received signal to detect a predetermined characteristic within the received signal;
responsive to detecting the predetermined characteristic, analyzing the received signal to identify an event associated with the predetermined characteristic; and
performing an action based upon a type of the identified event.