Apparatus for identifying falls and activities of daily living

Abstract

The present invention provides and apparatus for distinguishing falls from activities of daily living (ADLs). First, the human movements and muscle activities would be obtained by an electromyography measuring unit and/or an inertia measuring unit to record ADLs, and falls would be distinguished from ADLs to trigger the protecting devices in time to prevent or decrease injury. In addition, the apparatus would be preset for different operational conditions to adapt different users by a setting unit to increase accuracy. Finally, the moving distance and the direction of the user would be obtained by the electromyography measuring unit and/or the inertia measuring unit to obtain the location thereof in an interior space.

1 . A recognition device, comprising:
 a physiological sensor unit measuring a physiological signal; and   a recognition unit determining whether a fall is going to happen through processing the physiological signal.   
     
     
         2 . The recognition device as claimed in  claim 1 , further comprising:
 an inertia sensor unit obtaining a motion signal provided to the recognition unit for determining whether the fall is going to happen; and   a computing unit computing the physiological signal and the motion signal to obtain a computed result.   
     
     
         3 . The recognition device as claimed in  claim 2 , wherein the recognition unit receives the computed result to determine whether the fall is going to happen. 
     
     
         4 . The recognition device as claimed in  claim 2 , wherein the inertia sensor unit is at least one of an accelerometer and a gyroscope. 
     
     
         5 . The recognition device as claimed in  claim 2  further comprising:
 a memory unit storing the computed result and a signal threshold; and 
 an output unit outputting the computed result and a determining result generated by the recognition unit, 
 
     
     
         6 . The recognition device as claimed in  claim 5 , wherein the signal threshold is generated by the computing unit based on the stored computing result. 
     
     
         7 . The recognition device as claimed in  claim 5  further comprising:
 a setting unit setting at least one of the physiological signal and the motion signal to be an exception signal representing a specific motion, wherein the specific motion represents a normal action for a specific controlled user but represents a comparable fall for a normal person. 
 
     
     
         8 . The recognition device as claimed in  claim 7 , wherein the signal threshold is one of respective signal thresholds of the physiological and the motion signals, and the recognition unit determines that the fall happens when at least one of the physiological signal and the motion signal is higher than the respective signal threshold and different from the exception signal. 
     
     
         9 . The recognition device as claimed in  claim 5  further comprising:
 a positioning unit obtaining a location of a specific controlled user in a space via processing an arrangement of the space and a distance having been moved and a moving direction of the specific controlled user in the space; and 
 a warning unit providing an information corresponding to the fall of the specific controlled user in the space, 
 wherein the output unit transmits the information to an institution for generating a medical suggestion, and the computing unit computes the physiological signal and the motion signal to obtain the distance having been moved and the moving direction. 
 
     
     
         10 . The recognition device as claimed in  claim 9 , wherein the information comprises a predictable injury corresponding to the location when the fall happens. 
     
     
         11 . The recognition device as claimed in  claim 1  further comprising:
 a protecting device being triggered to achieve a protecting effect when the fall happens. 
 
     
     
         12 . The recognition device as claimed in  claim 1 , wherein the physiological sensor unit is an electromyography sensor unit. 
     
     
         13 . The recognition device as claimed in  claim 12 , wherein the physiological sensor unit further comprises a health sensor unit, wherein the health sensor is at least one selected from a group consisting of a clinical thermometer, a sphygmomanometer, a glucometer, a pedometer, an oximeter, a electrocardiography and a electroencephalography. 
     
     
         14 . A fall positioning device, comprising:
 a sensor unit obtaining an sensor signal;   a recognition unit processing the sensor signal to determine whether a fall is going to happen; and   a positioning unit obtaining a location of a controlled user in a space via processing an arrangement of the space and a distance having been moved and a moving direction of the controlled user in the space.   
     
     
         15 . The fall positioning device as claimed in  claim 14  further comprising:
 a computing unit computing the sensor signal to obtain the distance having been moved and the moving direction and provide a computed result to the recognition unit for determining whether the fall is going to happen; 
 a warning unit providing an information corresponding to the fall of the controlled user in the space; and 
 an output unit transmitting the information to an institution to render a medical suggestion. 
 
     
     
         16 . The fall positioning device as claimed in  claim 15 , wherein the information comprises a predicted injury corresponding to the location when the fall happens, and the arrangement is a compartment configuration and furnishings of an interior space. 
     
     
         17 . The fall positioning device as claimed in  claim 16 , wherein the sensor unit is a physiological sensor unit. 
     
     
         18 . A fall recognition device, comprising:
 a setting unit setting a specific signal indicative of a specific motion to be an exception signal representing the specific motion of a specific controlled user, wherein the specific motion represents a normal action of the specific controlled user but represents the fall of a normal person; and   a recognition unit determining whether a fall is going to happen by taking the exception signal into consideration.   
     
     
         19 . The fall recognition device as claimed in  claim 18 , further comprising:
 a sensor unit obtaining a sensor signal; and   a computing unit computing the sensor signal and providing a result for the recognition unit to compare with the exception signal so as to determine whether the fall is going to happen.   
     
     
         20 . The fall recognition device as claimed in  claim 19 , wherein the fall is regarded as happening by the recognition unit when the sensor signal is different from the exception signal and is higher than a signal threshold. 
     
     
         21 . The fall recognition device as claimed in  claim 20 , wherein the signal threshold is a fall reference signal generated based on activities of daily living of the specific controlled user.