Lift monitoring system and method

• US 8,149,126 B2
• Filed: 01/30/2009
• Issued: 04/03/2012
• Est. Priority Date: 02/02/2007
• Status: Active Grant

• Current Assignee: Hartford Fire Insurance Company (The Hartford Financial Services Group, Inc.)
• Original Assignee: Hartford Fire Insurance Company (The Hartford Financial Services Group, Inc.)
• Inventors: Little, Thomas DC, Wagenaar, Robert Cornelis, Anthony, John J. III, Gingrave, Michael J.
• Primary Examiner(s): Bugg, George
• Assistant Examiner(s): MCNALLY, KERRI L
• Application Number:
  US12/362,737
• Publication Number:
  US 20090135009A1
• Time in Patent Office: 1,159 Days
• Field of Search: 340/540
• US Class Current: 340/573.7
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

Systems and methods are discussed for providing a sensor enhanced employee safety evaluation system. Systems that monitor and assess employee lifting behavior are employed at the workplace of an insured entity. Data from the lift monitoring systems are processed to obtain a safety evaluation. Based on the safety evaluation, the insurance provider can adjust the terms of the insurance policy to accurately reflect the risks associated with the insured entity. Feedback based on the safety evaluation is also provided to the insured entity and the employees of the insured entity to promote improvements in safe behavior.

Claims

1. A system for monitoring the lifting behavior of a subject comprising:

a wearable trunk sensor to be worn by the subject for measuring movement of a trunk of the subject and for outputting trunk sensor data indicative of measured trunk movement;

a wearable thigh sensor to be worn by the subject for measuring movement of a thigh of the subject and for outputting thigh sensor data indicative of measured thigh movement;

a computing device in communication with the trunk sensor and the thigh sensor configured for;

receiving the output trunk sensor data;

receiving the output thigh sensor data;

determining a trunk angle based on the received trunk sensor data;

determining a thigh angle based on the received thigh sensor data;

classifying subject movements as corresponding to one or more predetermined lifting strategies based on the determined trunk angle and thigh angle;

calculating a lift risk level associated with subject movements based on the determined trunk angle and thigh angles; and

outputting feedback indicative of at least one of i) a determination that the subject is employing an unsafe lifting strategy and ii) an incidence of a high-risk movement.

2. The system of claim 1, wherein the computing device outputs the feedback to the subject.

3. The system of claim 1, comprising an insurance business logic processor configured for receiving the feedback output by the computing device and for adjusting a parameter of an insurance policy based on the received feedback.

4. The system of claim 3, wherein the feedback received by the insurance business logic processor excludes any personally identifiable information associated with the subject.

5. The system of claim 1, wherein the feedback output by the computing device comprises exception data.

6. The system of claim 1, wherein the computing device is further configured to convert the determined trunk angle and the determined thigh angle into a trunk flexion value and a knee flexion value.

7. The system of claim 1, wherein the risk level calculation is further based on at least one of a weight of an object lifted by the subject, a horizontal distance the subject carries a lifted object, the vertical height the subject lifts an object, the stability of the object being lifted, locomotion data, ambient temperature, a slope of the ground upon which the subject lifts an object, a frequency with which the subject lifts objects, and the rate with which the subject lifts objects.

8. The system of claim 1, wherein:

the trunk sensor comprises an accelerometer,

the thigh sensor comprises an accelerometer,

the computing device determines the trunk angle based on acceleration data output by the trunk sensor; and

the computing device determines the thigh angle based on acceleration data output by the thigh sensor.

9. The system of claim 8, wherein the accelerometers in the thigh sensor and trunk sensor measure acceleration in at least two dimensions.

10. The system of claim 1, wherein the trunk sensor and thigh sensor each comprises an accelerometer and a gyroscope.

11. The system of claim 10, wherein the computing device determines the trunk angle based on acceleration and rotation data output by the trunk sensor and the thigh angle based on acceleration and rotation data output by the thigh sensor.

12. The system of claim 11, wherein for at least one of the thigh angle determination and the trunk angle determination, the computing device utilizes received acceleration data to correct for gyroscopic drift in received rotation data and wherein the angle determination is based on drift-corrected rotation data.

13. The system of claim 10, wherein the computing device is configured to calculate torso rotation of the subject by comparing the rotation data output by the trunk sensor with rotation data output by the thigh sensor.

14. The system of claim 1, wherein the risk level calculation is based in part on the lifting strategy employed by the subject.

15. The system of claim 1, wherein the risk level calculation is based in part on predetermined movement thresholds.

16. The system of claim 1, comprising a weight sensor in communication with the computing device for determining a weight of an object lifted by the subject and wherein the risk level calculation is further based on the determined object weight.

17. The system of claim 16, wherein the weight sensor comprises a pressure sensor for wirelessly transmitting pressure data to the computing device.

18. The system of claim 17, wherein the pressure sensor is configured for wearing within a shoe of the subject.

19. The system of claim 17, wherein the pressure sensor is configured for standing on by the subject.

20. The system of claim 17, wherein the pressure sensor is configured for measuring a distribution of weight the subject applies to the subject'"'"'s feet during a lift.

21. The system of claim 16, wherein the weight sensor comprises an RFID reader for interrogating RFID tags coupled to lifted objects and for extracting weight information from data retrieved from interrogated RFID tags.

22. The system of claim 1, wherein at least one of the thigh sensor and trunk sensor comprise a wireless transceiver configured for communication with the computing device according to the BLUETOOTH protocol.

23. The system of claim 1, wherein at least one of the thigh sensor and trunk sensor comprise a wireless transceiver configured for communication with the computing device according to one of the ANT, ANT+, and ZIGBEE protocols.

24. The system of claim 1, wherein the computing device and one of the thigh sensor and the trunk sensor share a common housing.

25. The system of claim 1, wherein the predetermined lifting strategies include stoop lifts and squat lifts.

26. The system of claim 25, wherein the predetermined lifting strategies further include a semi-squat lift.

27. The system of claim 1, wherein the predetermined lifting strategies include strategies that incorporate torso rotation.

28. The system of claim 1, wherein the computing device in communication with the trunk sensor and thigh sensor comprises a portable computing device.

29. A computerized method for monitoring the lifting behavior of a subject comprising:

receiving, from a wearable trunk sensor worn by the subject, trunk sensor data indicative of trunk movement measured by the trunk sensor;

receiving by a transceiver, from a wearable thigh sensor worn by the subject, thigh sensor data indicative of thigh movement measured by the thigh sensor;

determining, by a portable computing device, a trunk angle based on the received trunk sensor data;

determining, by the portable computing device, a thigh angle based on the received thigh sensor data;

calculating, by the portable computing device, a lift risk level associated with subject movements based on the determined trunk angle and thigh angle,

outputting, by the portable computing device, feedback indicative of an incidence of a high-risk movement.

30. The computerized method of claim 29, wherein the portable computing device outputs the feedback to the subject.

31. The computerized method of claim 29, comprising:

receiving, by an insurance business logic processor, the feedback output by the portable computing device; and

adjusting, by the insurance business logic processor, a parameter of an insurance policy based on the received feedback.

32. The computerized method of claim 31, wherein the feedback received by the insurance business logic processor excludes any personally identifiable information associated with the subject.

33. The computerized method of claim 29, wherein the feedback output by the portable computing device comprises exception data.

34. The computerized method of claim 29, comprising converting, by the portable computer device, the determined trunk angle and the determined thigh angle into a trunk flexion value and a knee flexion value.

35. The computerized method of claim 29, wherein the risk level calculation is further based on at least one of a weight of an object lifted by the subject, a horizontal distance the subject carries a lifted object, the vertical height the subject lifts an object, the stability of the object being lifted, locomotion data, ambient temperature, a slope of the ground upon which the subject lifts an object, a frequency with which the subject lifts objects, and the rate with which the subject lifts objects.

36. The computerized method of claim 29, comprising classifying, by the portable computing device, subject movements as corresponding to one or more predetermined lifting strategies, and wherein the output feedback includes a determination that the subject is employing an unsafe lifting strategy.

37. The method of claim 29, wherein:

the trunk sensor data comprises data indicative of trunk acceleration in at least two dimensions,

the thigh sensor data comprises data indicative of thigh acceleration in at least two dimensions,

the portable computing device determines the trunk angle based on the trunk acceleration data; and

the portable computing device determines the thigh angle based on the thigh acceleration data.

38. The computerized method of claim 29, wherein:

the trunk sensor data comprises data indicative of trunk acceleration and torso rotation;

the thigh sensor data comprises data indicative of thigh acceleration and thigh rotation;

determining the trunk angle comprises determining the trunk angle based at least in part on trunk acceleration data and torso rotation data; and

determining the thigh angle comprises determining the thigh angle based at least in part on thigh acceleration data and thigh rotation data.

39. The computerized method of claim 38, wherein determining at least one of the thigh angle determination and the trunk angle comprises utilizing received acceleration data to correct for gyroscopic drift in received rotation data and determining the angle based on drift-corrected rotation data.

40. The computerized method of claim 38, comprising calculating torso rotation of the subject by comparing rotation data received from the trunk sensor with rotation data received from the thigh sensor.

41. The computerized method of claim 29, wherein the risk level calculation is based in part on one of a lifting strategy employed by the subject and predetermined movement thresholds.

42. The computerized method of claim 29, comprising receiving, by the portable computing device, object weight data indicative of the weight of an object being lifted from a weight sensor, and wherein calculating the risk level is further based on the weight of the object as indicated by the received object weight data.

43. The computerized method of claim 42, wherein the object weight data comprises pressure data received from one of a sensor coupled to a shoe worn by the subject and a sensor coupled to a floor on which the subject is standing.

44. The computerized method of claim 43, wherein the pressure data is indicative of a distribution of weight the subject applies to the subject'"'"'s feet during a lift.

45. The computerized method of claim 42, wherein receiving object weight data comprises interrogating an RFID tag coupled to an object being lifted by the subject and extracting object weight data from data received resulting from the interrogation.

46. The computerized method of claim 29, wherein at least one of the thigh sensor data and the trunk sensor data are received from at least one of the thigh sensor and the trunk sensor via a wireless transceiver configured for communication according to one of the BLUETOOTH, ANT, ANT+, and ZIGBEE protocols.

47. The computerized method of claim 29, wherein at least one of the thigh sensor and the trunk sensor share a common housing with the portable computing device.

48. The computerized method of claim 29, comprising classifying subject movements as corresponding to one or more predetermined lifting strategies based at least on the determined trunk angle and thigh angle, wherein the predetermined lifting strategies include at least stoop lifts, squat lifts, semi-squat lifts, and lifts including torso rotation.

49. The computerized method of claim 48, wherein the lift risk level associated with subject movements is further based on the lifting strategy employed by the subject.

50. A non transitory computer readable medium storing computer executable instructions, which, when executed, cause a portable computing device to:

receive by a transceiver, from a wearable trunk sensor worn by a subject, trunk sensor data indicative of trunk movement measured by the trunk sensor;

receive by a transceiver, from a wearable thigh sensor worn by the subject, thigh sensor data indicative of thigh movement measured by the thigh sensor;

determine a trunk angle based on the received trunk sensor data;

determine a thigh angle based on the received thigh sensor data;

calculate a lift risk level associated with subject movements based on the determined trunk angle and thigh angle,

classify subject movements as corresponding to one or more predetermined lifting strategies; and

output feedback to the subject indicative of at least one of i) a determination that the subject is employing an unsafe lifting strategy and ii) an incidence of a high-risk movement.

51. The non-transitory computer readable medium of claim 50, wherein the computer executable instructions cause the portable computing device to output the feedback to at least one of the subject and an insurance business logic processor configured for adjusting a parameter of an insurance policy based on the received feedback.

52. The non-transitory computer readable medium of claim 51, wherein the feedback output to the insurance business logic processor excludes any personally identifiable information associated with the subject.

53. The non-transitory computer readable medium of claim 50, wherein the feedback output by the portable computing device comprises exception data.

54. The non-transitory computer readable medium of claim 50, storing instructions, which when executed by the processor, cause the portable computing device to convert the determined trunk angle and the determined thigh angle into a trunk flexion value and a knee flexion value.

55. The non-transitory computer readable medium of claim 50, wherein the risk level calculation is further based on at least one of a weight of an object lifted by the subject, a horizontal distance the subject carries a lifted object, the vertical height the subject lifts an object, the stability of the object being lifted, locomotion data, ambient temperature, a slope of the ground upon which the subject lifts an object, a frequency with which the subject lifts objects, and the rate with which the subject lifts objects.

56. The non-transitory computer readable medium of claim 50, wherein

the trunk sensor data comprises data indicative of trunk acceleration in at least two dimensions,

the thigh sensor data comprises data indicative of thigh acceleration in at least two dimensions,

the portable computing device determines the trunk angle based on the trunk acceleration data;

and

the portable computing device determines the thigh angle based on the thigh acceleration data.

57. The non-transitory computer readable medium of claim 50, wherein:

the trunk sensor data comprises data indicative of trunk acceleration and torso rotation; and

the thigh sensor data comprises data indicative of thigh acceleration and thigh rotation;

wherein determining the trunk angle comprises determining the trunk angle based at least in part on trunk acceleration data and torso rotation data, and determining the thigh angle comprises determining the thigh angle based at least in part on thigh acceleration data and thigh rotation data.

58. The non-transitory computer readable medium of claim 57, wherein determining at least one of the thigh angle determination and the trunk angle comprises utilizing received acceleration data to correct for gyroscopic drift in received rotation data and determining the angle based on drift-corrected rotation data.

59. The non-transitory computer readable medium of claim 57, storing instructions, which when executed by the processor, cause the portable computing device to calculate torso rotation of the subject by comparing rotation data received from the trunk sensor with rotation data received from the thigh sensor.

60. The non-transitory computer readable medium of claim 50, wherein the risk level calculation is based in part on at least one of the lifting strategy employed by the subject and on predetermined movement thresholds.

61. The non-transitory computer readable medium of claim 50, storing instructions, which when executed by the processor, cause the portable computing device to receive object weight data indicative of the weight of an object being lifted from a weight sensor, and wherein calculating the risk level is further based on the weight of the object as indicated by the received object weight data.

62. The non-transitory computer readable medium of claim 61, wherein the object weight data comprises pressure data received from one of a sensor coupled to a shoe worn by the subject and a sensor coupled to a floor on which the subject is standing.

63. The non-transitory computer readable medium of claim 62, wherein the pressure data is indicative of a distribution of weight the subject applies to the subject'"'"'s feet during a lift.

64. The non-transitory computer readable medium of claim 61, wherein receiving object weight data comprises interrogating an RFID tag coupled to an object being lifted by the subject and extracting object weight data from data received resulting from the interrogation.

65. The non-transitory computer readable medium of claim 50, wherein at least one of the thigh sensor data and the trunk sensor data are received from at least one of the thigh sensor and the trunk sensor via a wireless transceiver configured for communication according to the BLUETOOTH, ANT, ANT+, and ZIGBEE protocols.

66. The non-transitory computer readable medium of claim 50, wherein at least one of the thigh sensor and the trunk sensor share a common housing with the portable computing device.

67. The non-transitory computer readable medium of claim 50, wherein the predetermined lifting strategies include stoop lifts, squat lifts, semi-squat lifts, and lifts including torso rotation.

68. A system for monitoring the lifting behavior of a subject comprising:

means for receiving, from a wearable trunk sensor worn by the subject, trunk sensor data indicative of trunk movement measured by the trunk sensor;

means for receiving, from a wearable thigh sensor worn by the subject, thigh sensor data indicative of thigh movement measured by the thigh sensor;

means for determining, by a portable computing device, a trunk angle based on the received trunk sensor data;

means for determining, by the portable computing device, a thigh angle based on the received thigh sensor data;

means for calculating, by the portable computing device, a lift risk level associated with subject movements based on the determined trunk angle and thigh angle,

means for classifying, by the portable computing device, subject movements as corresponding to one or more predetermined lifting strategies; and

means for outputting, by the portable computing device, feedback to the subject indicative of at least one of i) a determination that the subject is employing an unsafe lifting strategy and ii) an incidence of a high-risk movement.

69. The system of claim 68, comprising:

means for receiving, by an insurance business logic processor, the feedback output by the portable computing device; and

means for adjusting, by the insurance business logic processor, a parameter of an insurance policy based on the received feedback.

70. The system of claim 69, wherein the feedback received by the insurance business logic processor excludes any personally identifiable information associated with the subject.

71. The system of claim 68, wherein the feedback output by the portable computing device comprises exception data.

72. The system of claim 68, comprising means for converting, by the portable computer device, the determined trunk angle and the determined thigh angle into a trunk flexion value and a knee flexion value.

73. The system of claim 68, wherein the risk level calculation is further based on at least one of a weight of an object lifted by the subject, a horizontal distance the subject carries a lifted object, the vertical height the subject lifts an object, the stability of the object being lifted, locomotion data, ambient temperature, a slope of the ground upon which the subject lifts an object, a frequency with which the subject lifts objects, and the rate with which the subject lifts objects.

74. The system of claim 68, wherein:

the trunk sensor data comprises data indicative of trunk acceleration in at least two dimensions,

the thigh sensor data comprises data indicative of thigh acceleration in at least two dimensions,

the portable computing device determines the trunk angle based on the trunk acceleration data; and

the portable computing device determines the thigh angle based on the thigh acceleration data.

75. The system of claim 68, wherein:

the trunk sensor data comprises data indicative of trunk acceleration and torso rotation; and

the thigh sensor data comprises data indicative of thigh acceleration and thigh rotation,

wherein determining the trunk angle comprises determining the trunk angle based at least in part on trunk acceleration data and torso rotation data, and determining the thigh angle comprises determining the thigh angle based at least in part on thigh acceleration data and thigh rotation data.

76. The system of claim 75, wherein determining at least one of the thigh angle determination and the trunk angle comprises utilizing received acceleration data to correct for gyroscopic drift in received rotation data and determining the angle based on drift-corrected rotation data.

77. The system of claim 75, further comprising:

calculating a torso rotation of the subject by comparing rotation data received from the trunk sensor with rotation data received from the thigh sensor.

78. The system of claim 68, wherein the risk level calculation is based in part on at least one of the lifting strategy employed by the subject and predetermined movement thresholds.

79. The system of claim 68, further comprising:

receiving, by the portable computing device, object weight data indicative of the weight of an object being lifted from a weight sensor, and wherein calculating the risk level is further based on the weight of the object as indicated by the received object weight data.

80. The system of claim 79, wherein the object weight data comprises pressure data received from one of a sensor coupled to a shoe worn by the subject and a sensor coupled to a floor on which the subject is standing.

81. The system of claim 80, wherein the pressure data is indicative of a distribution of weight the subject applies to the subject'"'"'s feet during a lift.

82. The system of claim 79, wherein receiving object weight data comprises interrogating an RFID tag coupled to an object being lifted by the subject and extracting object weight data from data received resulting from the interrogation.

83. The system of claim 68, wherein at least one of the thigh sensor data and the trunk sensor data are received from at least one of the thigh sensor and the trunk sensor via a wireless transceiver configured for communication according to one of the BLUETOOTH, ANT, ANT+, and ZIGBEE protocols.

84. The system of claim 68, wherein at least one of the thigh sensor and the trunk sensor and the portable computing device share a common housing.

85. The system of claim 68, wherein the predetermined lifting strategies include stoop lifts, squat lifts, semi-squat lifts, and lifts including torso rotation.