Einige Inhalte dieser Anwendung sind momentan nicht verfügbar.
Wenn diese Situation weiterhin besteht, kontaktieren Sie uns bitte unterFeedback&Kontakt
1. (WO2005046433) LIFE SIGN DETECTION AND HEALTH STATE ASSESSMENT SYSTEM
Anmerkung: Text basiert auf automatischer optischer Zeichenerkennung (OCR). Verwenden Sie bitte aus rechtlichen Gründen die PDF-Version.
byte 8 = respiration rate, where
0 through 100 = respiration rate, in breaths per minute
250 = cannot determine respiration rate (e.g. too much noise)
byte 9 = confidence score of the overall health state assessment
byte 10 = spare byte available for debug, testing, or future use

The checksum is a 16-bit summation of each of the data bytes. The summing is done

byte- wide, but the result is 16-blts wide.
All multi-byte entities are transmitted little-endian (lowest byte first). The only data that

is affected by this mle is the 16-bit checksum since all other protocol elements are bytes. Orientation is inteφreted using the diagram of Figure 33.
What is claimed is:
1. A life signs detection system for monitoring subjects, said system comprising a plurality of wearable platfoπns, each wearable platfoπn comprising

a sensor subsystem having a respiration rate sensor that detects abdominal
motion of a subject,

a processor, and
a transmitter for local sensor data of medical state infomiation ,

a plurality of local hubs each comprising

a separate wearable package comprising

a local transceiver hub accepting connection from an external
display and comprising
a receiver for local sensor data from said wearable platfoπns,

a remote base station receiving information from a plurality of local hubs and

comprising said external display, and a rule processing engine comprising
a processor executing a health state assessment algorithm that performs a medical evaluation and determines a confidence level for the evaluation, said algorithm comprising a rale set to calculate a health state classification and indicator of confidence.

2. The life signs detection system of claim 1 wherein the processing engine employs a subject personal baseline dependent mle set and tabulated parameter values.

3. The life signs detection system of claim 1 wherein the transmitter of the wearable platform is a short range RF transmitter having low bandwidth output for local sensor data.

4. The life signs detection system of claim 1 wherein the local transceiver hub comprises a short range RF transceiver, a medium or long range transmitter/transceiver and a processor.

5. The life signs detection system of claim 1 wherein said local sensor data comprises periodic and on demand digital data packets of medical state infoπnation from said wearable platfoπns.

6. The life signs detection system of claim 1 wherein said remote base station is a PDA.

7. The life signs detection system of claim 1 wherein said algorithm estimates the likelihood of injury,

8. The life signs detection system of claim 1 wherein said algorithm estimates the likelihood of an injury and the nature of the injury

9. The life signs detection system of claim 1 wherein the processing engine employs a subject personal baseline dependent mle set.

10. The life signs detection system of claim 1 wherein said display comprises color coded health state classifications and decision confidence score.

11 A life signs detection system for monitoring subjects, said system comprising
a plurality of wearable platfonns, each wearable platform comprising
a sensor subsystem having a respiration rate sensor that detects abdominal motion
of a subject,
a processor, and
a transmitter for local sensor data of medical state information ,
a plurality of local hubs each comprising
a separate wearable package comprising
a local transceiver hub accepting connection from an external display and
comprising a receiver for local sensor data from said wearable platforms,
a remote base station receiving information from a plurality of local hubs and comprising said external display, and
a mle processing engine comprising
a processor executing a health state assessment algorithm that performs a medical evaluation and detennines a confidence level for the evaluation, said algorithm comprising a mle set to calculate a health state classification and indicator of confidence,
said mle set providing data prioritization deteimining the order for proceeding through data inteφretation rules for which value levels are predeteπnined,
said algorithm comprising inteφretation mles for each health state.

12. The life signs detection system of claim 11 wherein the processing engine employs a subject personal baseline dependent mle set and tabulated parameter values.

13. The life signs detection system of claim 11 wherein said algorithm comprises tabulated interpretation mles and tabulated boundary conditions and tabulated abnormal values for each personal baseline.

14. The life signs detection system of claim 11 wherein the transmitter of the wearable platfoπn is a short range RF transmitter having low bandwidth output for local sensor data.

15. The life signs detection system of claim 11 wherein the local transceiver hub comprises a short range RF transceiver, a medium or long range transmitter/transceiver and a processor.

16. The life signs detection system of claim 11 wherein said local sensor data comprises periodic and on demand digital data packets of medical state infonnation from said wearable platforms.
17. The life signs detection system of claim 11 wherein said remote base station is a PDA.

IS. The life signs detection system of claim 11 wherein said algorithm estimates the likelihood of injury,

19. The life signs detection system of claim 11 wherein said algorithm estimates the likelihood of an injury and the nature of the injury

20. The life signs detection system of claim 11 wherein the processing engine employs a subject personal baseline dependent mle set.

21. The life signs detection system of claim 11 wherein said display comprises color coded health state classifications and decision confidence score.

22. A life signs detection system for monitoring subjects, said system comprising
a plurality of wearable platfoπns, each wearable platfoπn comprising
a sensor subsystem having a respiration rate sensor that detects abdominal motion
of a subject,
a processor, and a transmitter for local sensor data of medical state information ,
a plurality of local hubs each comprising
a separate wearable package comprising
a local transceiver hub accepting connection from an external display and
comprising
a receiver for local sensor data from said wearable platforms,
a remote base station receiving information from a plurality of local hubs and comprising said external display, and
a mle processing engine comprising
a processor executing a health state assessment algorithm that perfoπns a medical evaluation and detennines a confidence level for the evaluation, said algorithm comprising a mle set to calculate a health state classification and indicator of confidence,
said mle set providing data prioritization detemiining the order for proceeding tlirough data interpretation mles for which value levels are predetermined,
said algorithm comprising inteφretation mles for each health state,
wherein the confidence level is based on the likelihood of new state transitions and utilizes decision matrices dependent upon the number of parameter values received in a predetermined time interval.

23. The life signs detection system of claim 22 wherein the processing engine employs a subject personal baseline dependent mle set and tabulated parameter values.

24. The life signs detection system of claim 22 wherein said algorithm comprises tabulated inteφretation mles and tabulated boundary conditions and tabulated abnormal values for each personal baseline.

25. The life signs detection system of claim 22 wherein the transmitter of the wearable platfoπn is a short range RF transmitter having low bandwidth output for local sensor data.

26. The life signs detection system of claim 22 wherein the local transceiver hub comprises a short range RF transceiver, a medium or long range fransmitter/transceiver and a processor.

27. The life signs detection system of claim 22 wherein said local sensor data comprises periodic and on demand digital data packets of medical state infoπnation from said wearable platfoπns.

28. The life signs detection system of claim 22 wherein said remote base station is a PDA

29. The life signs detection system of claim 22 wherein said algorithm estimates the likelihood of injury,

30. The life signs detection system f claim 22 wherein said algorithm estimates the likelihood of an injury and the nature of the injury

31. The life signs detection system of claim 22 wherein the processing engine employs a subject personal baseline dependent mle set.

32. The life signs detection system of claim 22 wherein said display comprises color coded health state classifications and decision confidence score.

33. A life signs detection system for monitoring subjects, said system comprising
a plurality of wearable platforms, each wearable platform comprising
a sensor subsystem having a respiration rate sensor that detects abdominal motion
of a subject,
a processor, and
a transmitter for local sensor data of medical state infoπnation ,
a plurality of local hubs each comprising
a separate wearable package comprising
a local transceiver hub accepting connection from an external display and
comprising
a receiver for local sensor data from said wearable platfoπns,
a remote base station receiving infoimation from a plurality of local hubs and comprising said external display, and
a mle processing engine comprising
a processor executing a health state assessment algorithm that performs a medical evaluation and detennines a confidence level for the evaluation, said algorithm comprising a mle set to calculate a health state classification and indicator of confidence, said mle set providing data prioritization determining the order for proceeding through data inteφretation mles for which value levels are predetermined,
said algorithm comprising inteφretation mles for each health state,
wherein the confidence level is based on the likelihood of new state transitions and utilizes decision matrices dependent upon the number of parameter values received in a predetermined time interval, said confidence score dependent upon
a parameter set
a state change score and
a data persistence score.

34. The life signs detection system of claim 33 wherein the processing engine employs a subject personal baseline dependent mle set and tabulated parameter values.

35. The life signs detection system of claim 33 wherein said algorithm comprises tabulated inteφretation mles and tabulated boundary conditions and tabulated abnormal values for each personal baseline.

36. The life signs detection system of claim 33 wherein the transmitter of the wearable platform is a short range RF transmitter having low bandwidth output for local sensor data.

37. The life signs detection system of claim 33 wherein the local transceiver hub comprises a short range RF transceiver, a medium or long range transmitter/transceiver and a processor.

38. The life signs detection system of claim 33 wherein said local sensor data comprises periodic and on demand digital data packets of medical state infoπnation from said wearable platfoπns.

39. The life signs detection system of claim 33 wherein said remote base station is a PDA

40. The life signs detection system of claim 33 wherein said algorithm estimates the likelihood of injury,

41. The life signs detection system of claim 33 wherein said algorithm estimates the likelihood of an injury and the nature of the injury

42. The life signs detection system of claim 33 wherein the processing engine employs a subject personal baseline dependent mle set.

43. The life signs detection system of claim 33 wherein said display comprises color coded health state classifications and decision confidence score.

44. A life signs detection system for monitoring one significant vital sign and one indirect life sign of subjects, said system comprising
a plurality of wearable platforms, each wearable platform comprising a sensor subsystem comprising
a heart rate sensor,
a body motion sensor
a respiration rate sensor, and
a temperature sensor,
wherein the respiration rate sensor detects motion of a subject,
a processor, and
a fransmitter for local sensor data of medical state infoπnation ,
a plurality of local hubs each comprising
a separate wearable package comprising
a local transceiver hub accepting connection from an external display and
comprising
a receiver for local sensor data from said wearable platforms,
a remote base station receiving infoimation from a plurality of local hubs and comprising said external display, and
a mle processing engine comprising
a processor executing a health state assessment algorithm that perfonns a medical evaluation and detennines a confidence level for the evaluation, said algorithm comprising a mle set to calculate a health state classification and indicator of confidence.

45. The life signs detection system of claim 44 wherein the processing engine employs a subject personal baseline dependent mle set and tabulated parameter values.

46. The life signs detection system of claim 44 wherein the respiration rate sensor detects abdominal motion of the subject.

47. The life signs detection system of claim 44 wherein said algorithm comprises tabulated interpretation mles and tabulated boundary conditions and tabulated abnoimal values for each personal baseline.

48. The life signs detection system of claim 44 wherein the transmitter of the wearable platfonn is a short range RF transmitter having low bandwidth output for local sensor data.

49. The life signs detection system of claim 44 wherein the local transceiver hub comprises a short range RF transceiver, a medium or long range transmitter/transceiver and a processor.

50. The life signs detection system of claim 44 wherein said local sensor data comprises periodic and on demand digital data packets of medical state information from said wearable platforms.

51. The life signs detection system of claim 44 wherein said remote base station is a PDA

52. The life signs detection system of claim 44 wherein said algorithm estimates the likelihood of injury,

53. The life signs detection system of claim 44 wherein said algorithm estimates the likelihood of an injury and the nature of the injury

54. The life signs detection system of claim 44 wherein the processing engine employs a subject personal baseline dependent mle set.

55. The life signs detection system of claim 44 wherein said display comprises color coded health state classifications and decision confidence score.

56. A life signs detection system for monitoring one significant vital sign and one indirect life sign of subjects , said system comprising
a plurality of wearable platfoπns, each wearable platform comprising
a sensor subsystem comprising
a heart rate sensor,
a body motion sensor
a respiration rate sensor, and
a temperature sensor,
wherein the respiration rate sensor detects motion of a subject,
a processor, and
a transmitter for local sensor data of medical state infoπnation ,
a plurality of local hubs each comprising
a separate wearable package comprising a local transceiver hub accepting connection from an external display and
comprising
a receiver for local sensor data from said wearable platforms,
a remote base station receiving infonnation from a plurality of local hubs and comprising said external display, and
a mle processing engine comprising
a processor executing a health state assessment algorithm that performs a medical evaluation and deteimines a confidence level for the evaluation, said algoritlim comprising a mle set to calculate a health state classification and indicator of confidence,
said rale set providing data prioritization deteπnining the order for proceeding tlirough data inteφretation mles for which value levels are predetermined,
said algorithm comprising interpretation rules for each health state.

57. The life signs detection system of claim 56 wherein the processing engine employs a subject personal baseline dependent mle set and tabulated parameter values.

58. The life signs detection system of claim 56 wherein the respiration rate sensor detects abdominal motion of the subject.

59. The life signs detection system of claim 56 wherein said algorithm comprises tabulated inteφretation mles and tabulated boundary conditions and tabulated abnormal values for each personal baseline.

6U. The life signs detection system of claim 56 wherein the transmitter of the wearable platfoim is a short range RF transmitter having low bandwidth output for local sensor data.

61. The life signs detection system of claim 56 wherein the local transceiver hub comprises a short range RF transceiver, a medium or long range transmitter/transceiver and a processor.

62. The life signs detection system of claim 56 wherein said local sensor data comprises periodic and on demand digital data packets of medical state information from said wearable platforms.

63. The life signs detection system of claim 56 wherein said remote base station is a PDA

64. The life signs detection system of claim 56 wherein said algorithm estimates the likelihood of injury,

65. The life signs detection system of claim 56 wherein said algorithm estimates the likelihood of an injury and the nature of the injury

66. The life signs detection system of claim 56 wherein the processing engine employs a subject personal baseline dependent mle set.

67. The life signs detection system of claim 56 wherein said display comprises color coded health state classifications and decision confidence score.

68. A life signs detection system for monitoring one significant vital sign and one indirect life sign of subjects, said system comprising
a plurality of wearable platforms, each wearable platfoim comprising
a sensor subsystem comprising
a heart rate sensor,
a body motion sensor
a respiration rate sensor, and
a temperature sensor,
wherein the respiration rate sensor detects motion of a subject,
a processor, and
a transmitter for local sensor data of medical state infonnation ,
a plurality of local hubs each comprising
a separate wearable package comprising
a local transceiver hub accepting connection from an external display and
comprising
a receiver for local sensor data from said wearable platfonns,
a remote base station receiving infonnation from a plurality of local hubs and comprising said external display, and
a mle processing engine comprising
a processor executing a health state assessment algorithm that perfoπns a medical evaluation and detennines a confidence level for the evaluation, said algoritlim comprising a mle set to calculate a health state classification and indicator of confidence, said mle set providing data prioritization determining the order for proceeding through data inteφretation mles for which value levels are predetermined,
said algorithm comprising inteφretation mles for each health state, and
wherein the confidence level is based on the likelihood of new state transitions and utilizes decision matrices dependent upon the number of parameter values received in a predetennined time interval.

69. The life signs detection system of claim 68 wherein the processing engine employs a subject personal baseline dependent mle set and tabulated parameter values.

70. The life signs detection system of claim 68 wherein the respiration rate sensor detects abdominal motion of the subject.

71. The life signs detection system of claim 68 wherein said algorithm comprises tabulated inteφretation mles and tabulated boundary conditions and tabulated abnoimal values for each personal baseline.

72. The life signs detection system of claim 68 wherein the transmitter of the wearable platfoim is a short range RF transmitter having low bandwidth output for local sensor data.

73. The life signs detection system of claim 68 wherein the local transceiver hub comprises a short range RF transceiver, a medium or long range transmitter/transceiver and a processor.

74. The life signs detection system of claim 68 wherein said local sensor data comprises periodic and on demand digital data packets of medical state information from said wearable platfoπns.

75. The life signs detection system of claim 68 wherein said remote base station is a PDA

76. The life signs detection system of claim 68 wherein said algorithm estimates the likelihood of injury,

77. The life signs detection system of claim 68 wherein said algorithm estimates the likelihood of an injury and the nature of the injury

78. The life signs detection system of claim 68 wherein the processing engine employs a subject personal baseline dependent rule set.

79. The life signs detection system of claim 68 wherem said display comprises color coded health state classifications and decision confidence score.

80. A life signs detection system for monitoring one significant vital sign and one indirect life sign of subjects, said system comprising
a plurality of wearable platfoπns, each wearable platfoim comprising
a sensor subsystem comprising
a heart rate sensor, a body motion sensor
a respiration rate sensor, and
a temperature sensor,
wherein the respiration rate sensor detects motion of a subject,
a processor, and
a transmitter for local sensor data of medical state infonnation ,
a plurality of local hubs each comprising
a separate wearable package comprising
a local transceiver hub accepting connection from an external display and
comprising
a receiver for local sensor data from said wearable platforms,
a remote base station receiving information from a plurality of local hubs and comprising said external display, and
a mle processing engine comprising
a processor executing a health state assessment algorithm that perfonns a medical evaluation and detennines a confidence level for the evaluation, said algorithm comprising a mle set to calculate a health state classification and indicator of confidence,
said mle set providing data prioritization detemiining the order for proceeding through data inteφretation rules for which value levels are predetermined,
said algorithm comprising inteφretation mles for each health state,
wherein the confidence level is based on the likelihood of new state transitions and utilizes decision matrices dependent upon the number of parameter values received in a predetermined time interval, said confidence score dependent upon a parameter set
a state change score and
a data persistence score.
S 1. The life signs detection system of claim 80 wherein the processing engine employs a subject personal baseline dependent mle set and tabulated parameter values.

82. The life signs detection system of claim 80 wherein the respiration rate sensor detects abdominal motion of the subject.

83. The life signs detection system of claim 80 wherein said algoritlim comprises tabulated inteφretation mles and tabulated boundary conditions and tabulated abnoπnal values for each personal baseline.

84. The life signs detection system of claim 80 wherein the transmitter of the wearable platfonn is a short range RF transmitter having low bandwidth output for local sensor data.

85. The life signs detection system of claim 80 wherein the local transceiver hub comprises a short range RF transceiver, a medium or long range transmitter/transceiver and a processor.

86. The life signs detection system of claim 80 wherein said local sensor data comprises periodic and on demand digital data packets of medical state information from said wearable platforms.

87. The life signs detection system of claim 80 wherein said remote base station is a PDA

88. The life signs detection system of claim 80 wherein said algorithm estimates the likelihood of injury,

89. The life signs detection system of claim 80 wherein said algorithm estimates the likelihood of an injury and the nature of the injury

90. The life signs detection system of claim 80 wherein the processing engine employs a subject personal baseline dependent mle set.

91. The life signs detection system of claim 80 wherein said display comprises color coded health state classifications and decision confidence score.

92. A life signs detection system (LSDS) for monitoring one significant vital sign and one indirect life sign of a subject, said system comprising
a plurality of wearable platfoπns, each wearable platfonn comprising
a sensor subsystem comprising
a heart rate sensor,
a body motion sensor
a respiration rate sensor, and
a temperature sensor, wherein the respiration rate sensor detects abdominal motion and is capable of
detecting motion of the subject,
a processor
a short range RF transmitter having low bandwidth output for local sensor data, a plurality of local hubs each comprising
a separate wearable package comprising
a local transceiver hub comprising
a short range RF transceiver
a medium or long range transmitter/transceiver, and
a processor
said separate wearable package accepting connection from one or more external
displays and comprising
a receiver for local sensor data comprising
periodic and on demand digital data packets of medical state
infoπnation from said wearable platforms and,
a remote base station receiving information from a plurality of local hubs and comprising an external display,
wherein the remote base station is a PDA, and
a mle processing engine comprising
a processor executing a health state assessment algorithm, wherein said algorithm estimates the likelihood of injury and the nature of an injury, perfonns a medical evaluation and determines a confidence level for each of multiple measurements, said algorithm comprising
a processing engine employing a subject personal baseline dependent rale set and
tabulated parameter values
to calculate and display color-coded health state classification and indicators of confidence, detemiining physiologic state, decision confidence score and triage indications,
said mle set providing data prioritization deteimining the order for proceeding tlirough data inteφretation mles for which value levels are predetennined,
said algorithm comprising tabulated inteφretation mles for each health state and applying tabulated boundary conditions and tabulated abnoimal values for each personal baseline,
wherein the confidence level is based on the likelihood of new state transitions and utilizes decision matrices dependent upon the number of parameter values received in a predetennined time interval, said confidence level dependent upon
a parameter set
a state change score and
a data persistence score.

93. A system for processing information on the physical status of one or more subjects comprising
apparatus for transmitting infoimation comprising
a canier for sensors ananged to be worn by the subjects for providing electrical signals including amplitude and duration values representative of physical parameters of the subjects, and
a host receiver having a processor that deteimines whether the amplitude and duration values fall within acceptable limits.

94. The system for processing infoimation on the physical status of one or more subjects of claim 93, having a communications protocol that assigns a set of sensors to a single hub, and a set of hubs to a single remote station.

95. The system for processing infoimation on the physical status of one or more subjects of claim 94, wherein a local protocol provides the transport of data between one or more sensors and a single hub.

96. The system for processing information on the physical status of one or more subjects of claim 95, said system comprising a plurality of sensors, and wherein a local data packet fonnat is extensible, not requiring changes to the hub to accommodate new sensor additions.

97. The system for processing infoπnation on the physical status of one or more subjects of claim 96, wherein gaps in the sensor data are accounted for by providing a filler packet, or by the indication that the sensor is no longer communicating.

98. The system for processing information on the physical status of one or more subjects of claim 96, wherein the filler packet comprises a timestamp.

99. The system for processing infonnation on the physical status of one or more subjects of claim 98, wherein a distant protocol provides the transport of data between a hub, and the remote station.

100. The system for processing infonnation on the physical status of one or more subjects of claim 99, wherein the distant protocol allows for intemuptions in the data stream, with later recovery of data stored within the hub.

101. The system for processing infonnation on the physical status of one or more subjects of claim 100, wherein the host receiver is comprised within a hub system that has a user interface that provides a local health display, wherein the host receiver further comprises a local selection mechanism to facilitate the initial association of one or more sensors to a specific hub.

102. The system for processing infomiation on the physical status of one or more subjects of claim 93, wherein the association of a specific hub to a remote station is perfoimed at the hub, or via a remote communications link, either to a medic PDA, or back to a remote station.

103. The system for processing information on the physical status of one or more subjects of claim 102, wherein the remote subsystem has a ser interface that displays the basic status of multiple hubs within a single display.

104. The system for processing information on the physical status of one or more subjects of claim 103, further comprising a display of status and data details from at least a single hub.

105. The system for processing infoπnation on the physical status of one or more subjects of claim 103, further comprising a medic PDA subsystem that has a user interface for displaying a list of hubs to connect to, and a mechanism to connect and display the detailed data as delivered by the hub.

106. The system for processing infonnation on the physical status of one or more subjects of claim 93, wherein a mnning average of the amplitude and duration values of a group of previous respiration cycles is transmitted to the host processor, wherein a small hysteresis value is applied to the respiration signal to minimize false "end of cycle" readings due to noise in the signal, and wherein said hysteresis value is dynamically adjusted based on the amplitude of the previous cycle.

107. A heart rate trend tracking algorithm, comprising mnning in parallel
a first process that tracks an already established trend,
a second process that looks for a new trend, and
a third process that detennines which of the first and second processes has better data.

108. The heart rate trend tracking algorithm of claim 107, wherein before presenting incoming

EKG data to the first process, it is filtered and noise corrected.

109. A heart rate trend tracking algoritlim comprising
filtering and canceling noise from incoming EKG data
presenting the data to trend tracking routines comprising
a first process that tracks an already established trend,
a second process that looks for a new trend, and a third process that determines which of the first and second processes has better data, several times a second making a decision to keep using an existing trend or to shift to using a new trend
averaging and filtering the EKG data, and
converting the data into a beats-per-second value.

110. The heart rate calculation algorithm of claim 109, wherein each incoming EKG pulse is time stamped, and those remaining after filtering and noise cancellation are processed in non-real-time.

111. A method for transmitting infoπnation on the physical status of a subject comprising mnning an algorithm comprising the steps of
looking for a new trend by
looking at four most recent inter-beat intervals and
developing a scoring based on the consistency of these intervals.

112. The method for transmitting infoimation on the physical status of a subject of claim 11 1, further comprising using a window size of +/- 12.5%

113. The method for transmitting infonnation on the physical status of a subject of claim 111, wherein only consistent inter-beat intervals are saved in a history aπay.

114. The method for transmitting information on the physical status of a subject of claim 111, wherein an existing trend is tracked by
assuming the heart rate to be at a certain frequency, and
looking for more heartbeats at these expected intervals,
ignoring extra pulses are ignored
inserting missing pulses.

115. The method for transmitting infonnation on the physical status of a subject of claim 111, wherein an existing trend process is locked onto a new trend when that new trend is seen to be strong and stable comprising
maintaining a score for how well the trend is being tracked.
unlocking the existing trend when its score is low, and then
locking onto a new trend when the new trend is seen to exist.

116. The method for transmitting infoπnation on the physical status of a subject of claim 115, wherein an anay of inter-beat intervals is maintained in order to provide the averaging process the infoπnation it needs.

117. The method for transmitting infoimation on the physical status of a subject of claim 1 15, wherein if both the trend the trend tracking and acquisition processes have low scores, the heart rate status is set to "unstable".

118. The method for transmitting infonnation on the physical status of a subject of claim 115, wherein if there are no heartbeats but the EKG contacts are determined to be on-body, then the heart rate status is set to indicate "none".

119. The method for transmitting information on the physical status of a subject of claim 115, wherein an averaging filter looks back in time through an anay of historic inter-beat intervals until it sees at least 4 seconds of pulse timing, and then averages this most recent pulse timing.

120. The method for transmitting infoimation on the physical status of a subject of claim 115, wherein a low pass filter stage limits how fast the heart rate can change, wherein, the rate at which the reported heart rate is allowed to approach the calculated heart rate based on the old and new trends is limited to 4 BPM per second.

121. An apparatus for transmitting infoimation on the physical status of a subject comprising a canier for sensors ananged to be worn by the subject for providing electrical signals representative of physical parameters of the subject, said canier comprising
a central housing,
two flexible extensions containing external sensors, and
a harness, and
electronics residing on a PC board to receive and inteφret the electrical signals from the sensors, and to process the signals at the location of the subject and send it wirelessly to a local receiver or transceiver for retransmission to a separate computer station,
said electronics measures life signs comprising heart rate by detecting and timing EKG R-waves,
physical activity and orientation from signals provided by an accelerometer,
respiration rate by reading a chest expansion sensor, and
temperature.

122. The apparatus for transmitting infoπnation on the physical status of a subject of claim

121, further comprising electronics to analyzing the life signs using a health state deteimination algorithm and transmitting the resulting health indication, plus the raw data behind it out of the sensor.

123. The apparatus for transmitting infonnation on the physical status of a subject of claim

122, wherein the transmission is to a local receiver approximately every two seconds.

124. An electronics package for an apparatus for transmitting infoimation on the physical status of a subject, comprising
a microprocessor having
low power draw,
program memory,
RAM memory,
EEPROM for non- volatile storage,
general purpose I/O,
analog inputs,
external interrupts, timers,
high and low speed clocks,
low-power sleep modes,
in-circuit piOgrammability, and
development tools.

125. The electronics package for an apparatus for transmitting information on the physical status of a subject of claim 124, wherein the microprocessor employs sleep modes, wherein a high speed crystal runs the processor when it is awake, and a lower-frequency crystal keeps the internal timers running when both awake and in a low-power standby mode.

126. The electronics package for an apparatus for transmitting infomiation on the physical status of a subject of claim 124, wherein the apparatus comprises sensors and the output of the sensors is transmitted to a local receiver for further transmission to a more remote station, said sensors comprising a flex sensor with a variable resistance, that is changed by the electronics into a voltage that is frequency limited using a band pass filter and sampled by the processor using one of its built-in analog-to-digital inputs.

127. The electronics package for an apparatus for transmitting infoπnation on the physical status of a subject of claim 126, further comprising an RF transmitter, wherein a 1 kHz
Manchester-encoded data stream is sent out the RF transmitter once every two seconds.

128. The electronics package for an apparatus for transmitting infonnation on the physical status of a subject of claim 127, wherein the transmitter uses simple on-off keying, thus only drawing power when transmitting a "1".

129. The electronics package for an apparatus for transmitting infonnation on the physical status of a subject of claim 127, wherein activity is measured periodically in order to deteπnine how much movement the user is experiencing by turning on the accelerometer and sampling its output at a looking for the highest amount of acceleration that is sampled, and holding that level for a few seconds.

130. A method for transmitting infomiation on the physical status of a subject, wherein
a bandwidth limited chest expansion voltage of a respiration monitor is sampled,
an algorithm determines when the wearer is inhaling or exhaling by looking at the relative change in the sampled signal, effectively taking a first order derivative that removes the DC component of the signal,
timing an analyzing a binary signal (inhaling or exhaling) for consistent behavior,
if several similar (+/- 25%) timed breaths are seen, they are averaged together and used as the final respiration value,
if no consistent breaths are seen in a 30 second period, the respiration rate is set to "unstable",
if no chest expansion/contraction is seen for over a minute, respiration rate is set to zero.

131. A system for processing information on the physical status of one or more subjects comprising
a sensor subsystem designed to:
capture and convert the analog data into digital foπn,
perform enor detection processing,
validate the proper application and operation of hardware systems, perfoπn combined analysis of the biometric data, yielding the overall health metric,
assemble and transmit periodic data packets to the hub subsystem, and
accept data received from the hub subsystem, applying configuration or command sets to update operational parameters, and
a hub subsystem designed to:
collect periodic data from the sensor subsystem(s),
buffer samples for transmission to the remote station;
provide minimal user interface capabilities to display the overall health status, and allow for sensor subsystem selection to be performed;
perform additional health status processing if multiple sensors are available to a single hub;
provide the uplink processing and data packaging for remote/PDA accesses, and a remote subsystem designed to:
provide status display of multiple hubs;
provide expanded status display of one selected hub; and
provide long-teim data logging for all hubs connected.

132. A system for processing infoimation on the physical status of one or more subjects comprising
a first protocol for transfening data from a vital signs sensor to a hub, which comprises a concentrator and gateway to a remote station and
a second protocol for transfening data between the hub, and a remote viewing station that may be either a medic PDA, or a grouped display.

133. The system for processing infomiation on the physical status of one or more subjects of claim 132, wherein the first protocol provides communications locally between one or more body- worn sensors, and a physically proximate hub/gateway.

134. The system for processing infonnation on the physical status of one or more subjects of claim 133, wherein the data transmitted from the sensor to the hub comprises sensor data and control data.

135. The system for processing information on the physical status of one or more subjects of claim 134, wherein the sensor data contains the data values obtained from one or more vital signs sensors that are present and the control data is sent in response to a command from the hub.

136. An apparatus for transmitting infonnation on the physical status of a subject comprising a 32 Hz clock as the basic timer, and
a processor mnning an algorithm that looks at 4 seconds or more of EKG data to determine trends and includes filtering trend tracking and analysis, executed at an 8 Hz rate, wherein averaging/filtering is mn once every two seconds, and the resulting EKG rate is converted to a beats-per-second value every two seconds.
Algorithm specifics

137. A method for transmitting infonnation on the physical status of a subject comprising interrupting a processor when EKG electrical impulses of sufficient magnitude anive, time stamping every intermpt and saving a record of its having happened
stop recording interrupts if too many EKG pulses are still waiting processing by the filtering process
periodically clearing the list of pending interrupts
removing presumably inconect EKG infoimation by applying low pass filtering and noise cancellation.

138. The method for transmitting infonnation on the physical status of a subject of claim 137, wherein the low pass filter discards incoming pulses that occur less than 125 msec after the previous good pulse.

139. A system for processing infoimation on the physical status of one or more subjects comprising
a sensor in canier for sensors that communicates wirelessly with a health hub comprising a device having a processor.

140. The system for processing information on the physical status of one or more subjects of claim 139, further comprising a RF transceiver operating at the same frequency at both ends of the wireless link sending Manchester encoded data.

141. The system for processing infonnation on the physical status of one or more subjects of claim 139, wherein the infomiation is sent in packets with enor conection bits.

142. A system for processing infoimation on the physical status of one or more subjects comprising a health status algoritlim that
receives copies of the newly received data,
places the data into individual parameter data buffers
executes once per second, the health status algoritlim on the data buffers,
updates the display of the health status, along with the confidence score of that deteimination.

143. The system for processing information on the physical status of one or more subjects of claim 142, wherein the health status algorithm comprises the steps of:
data gathering and buffering;
data averaging and conversion from numeric/symbolic into qualified range data;
mle lookup processing;
confidence scoring; and
result display.

144. The system for processing infomiation on the physical status of one or more subjects of claim 142, wherein the step of data gathering and buffering comprises
incrementing once per second the cunent sample index of these buffers, and

new sample index flags are cleared.

145. The system for processing information on the physical status of one or more subjects of claim 143, wherein the conversion from source data to qualified data comprises
processing each parameter ring buffer to provide the average value of the data within the ring buffer,
comparing the average value to defined range boundaries, and
returning a qualified data range value.

146. The system for processing infonnation on the physical status of one or more subjects of claim 143, wherein mle lookup processing comprises
having a bitmap of qualified data range results for each parameter, along with a result state to be used when a match is found,
once the cunent states of the ring buffers has been obtained, these states are compared to each mle until either a match is detected, in which case the conesponding health state is used, or all rules have been checked, in which case a default state is used.

147. The system for processing infomiation on the physical status of one or more subjects of claim 143, wherein confidence scoring comprises
detemiining whether or not the current health state has changed,
determining the health state and confidence score, displaying new values on the main dialog, in Hub Health State and Hub
Confidence fields.

148. The system for processing infoimation on the physical status of one or more subjects of claim 130, further comprising a medic PDA subsystem designed to establish a communications link to a single hub unit; and provide display of all available sensor data and status infonnation.

Table 1. LSDS Platform Parameters and Error Conditions
Table 2. Default Health State Classification Descriptions

Table 3. Default Life Signs Inteφretation Rules for Alive/Green and Dead/Red States
BPM) and (RR <30 breaths/minute Temp ≠ NORMAL)] for 4 minutes
and RR ≥ 8 breaths/minutes) and or more
(Temp is NORMAL)] for 8 seconds
or more
HR, Acceleration/Position and Temp [(HR < 160 BPM and HR > 40 [(HR = 0) and (Acceleration is
BPM) and (any acceleration value NONE for any position value) and
and any position value) and Temp Temp ≠ NORMAL )] for 4 minutes
is NORMAL] for 8 seconds or more
[(HR > 160 /BPM and HR < 220
BPM) and (RR >30 breaths per
minute and RR ≤ 45 breaths per
minute) and (Acceleration is Fast,
for any Position value) and Temp is
NORMAL] for 8 seconds or more

RR, Acceleration /Position and Temp [(RR <30 breaths/minute and RR > [(RR = 0) and (Acceleration =
8 breaths/minutes) and (any NONE for any Position value) and
acceleration value and any position Temp ≠ NORMAL)] for 5 minutes
value) and Temp is NORMAL] for or more
8 seconds or more
[(RR >30 breaths per minute and
RR < 45 breaths per minute) and
(Acceleration is Fast, for any
Position value) and Temp is
NORMAL] for 8 seconds or more
HR, RR, Acceleration /Position and [(HR < 160 BPM an HR > 40 [(HR = 0) and (RR = 0) and Temp BPM) and (RR <30 breaths/minute (Acceptation is NONE for any
and RR > 8 breaths/minutes) and Position value) and Temp ≠
(any acceleration value and any NORMAL] for 4 minutes or moie
position value) and Temp is
NORMAL] for 8 seconds or more
[(HR > 160 /BPM and HR < 220
BPM) and (RR >30 breaths per
minute and RR < 45 breaths per
minute) and Acceleration is Fast,
for any Position value) and Temp is
NORMAL] for 8 seconds or more

Table 4. Default Life Signs Inteφretation Rules for Alive/Yellow State

Table 5. Default LSDS Alive/Normal Data Ranges

Table 6. Default LSDS Alive/Not-Normal Data Ranges

Table 8. Default Decision Matrix for Only One Parameter in Last Decision Interval

Table 9. Default Decision Matrix for Two Parameters in Last Decision Interval



orientation).



*Note that the fourth value range is only filled in for acceleration (acceleration and orientation)



*Note that the fifth value lange is only filled in for acceleiation (acceleration and orientation)

Table 12: State Change Score Components

Table 13, Persistence Score Components

Table 14. Components of Weight (Multiplier) by Parameter Set

Table 15. Confidence Score Ranges

Body Area Network (BAN)
Personal Area Network (PAN)

LSDS Monitor
Sensor Array
• Heart Rate
• Respiration
• Skin Temperature
• Acceleration
• Body Orientation
Software
• Enhanced Signal Processing for
Noise Reduction
• Health State Assessment Algorithm
(Primary Rule Set)

Communications Gateway
Wireless Transmitter
Wireless Receiver (Optional)
On -board Display (Optional)
Extended Data Storage
Query Response Software

Local Area Network (LAN) or Wide Area Network (WAN)

Remote Assessment/Dispatch Station
Data Storage Connectivity {E.g., patient records or full disclosure database)

Wide Area Alarm System (Optional)
Software
Health State Assessment Algorithm (Multi-tier processing)
Advanced Clinical Analysis Software (Optional)
System Overview Module (Displays status for all active monitors)
Single Patient Detail/Analysis/Query Module
Interface to Medic Dispatch Decision Software (Optional)
Interface to Emergency Response Database (Optional)
Interface to Emergency Room Management Software (Optional)
Interface to Disaster Management System (Optional)

Figure 48 - Block Diagram :Life Signs Detection System