Techniques for prediction and monitoring of clinical episodes

• US 20060241510A1
• Filed: 08/03/2005
• Published: 10/26/2006
• Est. Priority Date: 04/25/2005
• Status: Active Grant

• Current Assignee: Hill-Rom Services Incorporated (Baxter International Inc.)
• Original Assignee: EarlySense Ltd.
• Inventors: Pinhas, Itzhak, Gross, Yosef, Halperin, Avner, Lange, Daniel H.
• Granted Patent: US 7,314,451 B2
• Time in Patent Office: Days
• US Class Current: 600/534
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/4094 Diagnosing or monitoring seizure diseases, e.g. epilepsy
• CPC Class Codes: A61B 5/6892 Mats
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

A method is provided for predicting an onset of an asthma attack. The method includes sensing at least one parameter of a subject without contacting or viewing the subject or clothes the subject is wearing, and predicting the onset of the asthma attack at least in part responsively to the sensed parameter. Also provided is a method for predicting an onset of an episode associated with congestive heart failure (CHF), including sensing at least one parameter of a subject without contacting or viewing the subject or clothes the subject is wearing, and predicting the onset of the episode at least in part responsively to the sensed parameter. Other embodiments are also described.

Claims

1-55. -55. (canceled)

56. A method for predicting an onset of an asthma attack, comprising:

sensing at least one parameter of a subject without contacting or viewing the subject or clothes the subject is wearing; and

predicting the onset of the asthma attack at least in part responsively to the sensed parameter.

57. The method according to claim 56, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein sensing the at least one parameter comprises sensing the at least one motion-related parameter.

58. The method according to claim 56, wherein predicting the onset comprises predicting the onset before the subject or a caretaker of the subject becomes aware of the onset.

59. The method according to claim 56, wherein predicting the onset comprises generating subject-specific data regarding the parameter by analyzing previous occurrences of the asthma attack, and predicting the onset at least in part responsively to the data.

60. The method according to claim 56, wherein predicting the onset comprises determining a measure of restlessness of the subject, and predicting the onset at least in part responsively to the measure of restlessness.

61. The method according to claim 56, comprising determining a measure of coughing of the subject, wherein predicting the onset comprises predicting the onset at least in part responsively to the sensed parameter and the measure of coughing.

62. The method according to claim 56, wherein sensing the at least one parameter comprises sensing the at least one parameter without requiring human compliance.

63. The method according to claim 56, wherein sensing the at least one parameter comprises sensing the at least one parameter while the subject is sleeping.

64. The method according to claim 63, comprising alerting the subject to the predicted onset only after the subject awakes.

65. The method according to claim 56, wherein the at least one parameter includes at least one breathing-related parameter of the subject, and wherein sensing the at least one parameter comprises sensing the at least one breathing-related parameter.

66. The method according to claim 65,

wherein the at least one parameter includes at least one heartbeat-related parameter of the subject,

wherein sensing the at least one parameter comprises sensing the at least one heartbeat-related parameter, and

wherein predicting the onset of the asthma attack comprises predicting the onset of the asthma attack at least in part responsively to the breathing-related and the heartbeat-related parameters.

67. The method according to claim 65, wherein predicting the onset comprises:

determining at least one breathing pattern of the subject responsively to the sensed breathing-related parameter;

comparing the breathing pattern with a baseline breathing pattern; and

predicting the onset at least in part responsively to the comparison.

68. The method according to claim 56, wherein sensing the at least one parameter comprises measuring a pressure in, on, or under a reclining surface upon which the subject lies.

69. The method according to claim 68, wherein sensing the at least one parameter comprises measuring the pressure using exactly one sensor placed in, on, or under the reclining surface.

70. A method for predicting an onset of an episode associated with congestive heart failure (CHF), comprising:

sensing at least one parameter of a subject without contacting or viewing the subject or clothes the subject is wearing; and

predicting the onset of the episode at least in part responsively to the sensed parameter.

71. The method according to claim 70, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein sensing the at least one parameter comprises sensing the at least one motion-related parameter.

72. The method according to claim 70, wherein sensing the at least one parameter comprises measuring a pressure in, on, or under a reclining surface upon which the subject lies.

73. The method according to claim 70, wherein sensing the at least one parameter comprises sensing the at least one parameter while the subject is sleeping.

74. The method according to claim 70, wherein sensing the at least one parameter comprises sensing a breathing-related parameter of the subject, and a blood pressure of the subject, and wherein predicting the onset comprises predicting the onset at least in part responsively to the breathing-related parameter and the blood pressure.

75. The method according to claim 70, wherein sensing the at least one parameter comprises sensing the at least one parameter without requiring human compliance.

76-104. -104. (canceled)

105. A method for predicting an onset of a clinical episode, comprising:

sensing at least one parameter of a subject without requiring human compliance; and

predicting the onset at least in part responsively to the sensed parameter.

106. The method according to claim 105, wherein sensing the at least one parameter comprises sensing the at least one parameter without contacting or viewing the subject or clothes the subject is wearing.

107. The method according to claim 105, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein sensing the at least one parameter comprises sensing the at least one motion-related parameter without requiring human compliance.

108. The method according to claim 105, wherein sensing the at least one parameter comprises sensing the at least one parameter while the subject is sleeping, and comprising alerting the subject to the predicted onset only after the subject awakes.

109. The method according to claim 105, wherein sensing the at least one parameter without requiring human compliance comprises measuring a pressure in, on, or under a reclining surface upon which the subject lies.

110. The method according to claim 105, wherein the clinical episode includes an asthma attack, and wherein predicting the onset comprises predicting the onset of the asthma attack.

111. The method according to claim 105, wherein the clinical episode includes an episode associated with congestive heart failure (CHF) of the subject, and wherein predicting the onset comprises predicting the onset of the episode associated with the CHF.

112. The method according to claim 105, wherein the clinical episode includes an episode of hypoglycemia caused by diabetes, and wherein predicting the onset comprises predicting the onset of the episode of hypoglycemia.

113. The method according to claim 105, wherein the clinical episode is selected from the list consisting of:

an episode of abnormal autonomic nervous system activity caused by a neurological condition, an epileptic seizure, an episode of Periodic Limb Movements in Sleep (PLMS), a stroke, an episode of essential tremor, an episode of stress, an episode of fibrillation, an episode associated with chronic obstructive pulmonary disease (COPD), an episode associated with cystic fibrosis (CF), and an episode of anaphylactic shock, and wherein predicting the onset comprises predicting the onset of the selected clinical episode.

114. The method according to claim 105, wherein the at least one parameter includes at least one breathing-related parameter of the subject, and wherein sensing the at least one parameter comprises sensing the at least one breathing-related parameter without requiring human compliance.

115. The method according to claim 114, wherein predicting the onset comprises:

determining at least one breathing pattern of the subject responsively to the sensed breathing-related parameter;

comparing the breathing pattern with a baseline breathing pattern; and

predicting the onset at least in part responsively to the comparison.

116-138. -138. (canceled)

139. Apparatus for predicting an onset of an asthma attack, comprising:

a non-contact sensor, adapted to sense at least one parameter of a subject without contacting the subject or clothes the subject is wearing; and

a control unit, adapted to predict the onset of the asthma attack at least in part responsively to the sensed parameter.

140. The apparatus according to claim 139, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein the sensor is adapted to sense the at least one motion-related parameter.

141. The apparatus according to claim 139, wherein the control unit is adapted to predict the onset before the subject or a caretaker of the subject becomes aware of the onset.

142. The apparatus according to claim 139, wherein the control unit is adapted to generate subject-specific data regarding the parameter by analyzing previous occurrences of the asthma attack, and to predict the onset at least in part responsively to the data.

143. The apparatus according to claim 139, wherein the control unit is adapted to determine a measure of restlessness of the subject, and to predict the onset at least in part responsively to the measure of restlessness.

144. The apparatus according to claim 139, wherein the control unit is adapted to determine a measure of coughing of the subject, and to predict the onset at least in part responsively to the sensed parameter and the measure of coughing.

145. The apparatus according to claim 139, wherein the sensor is adapted to sense the at least one parameter without requiring human compliance.

146. The apparatus according to claim 139, wherein the sensor is adapted to sense the at least one parameter while the subject is sleeping.

147. The apparatus according to claim 146, comprising a user interface, wherein the control unit is adapted to drive the user interface to alert the subject to the predicted onset only after the subject awakes.

148. The apparatus according to claim 139, wherein the at least one parameter includes at least one breathing-related parameter of the subject, and the sensor is adapted to sense the at least one breathing-related parameter.

149. The apparatus according to claim 148,

wherein the at least one parameter includes at least one heartbeat-related parameter of the subject,

wherein the sensor is adapted to sense the at least one heartbeat-related parameter, and

wherein the control unit is adapted to predict the onset of the asthma attack at least in part responsively to the breathing-related and heartbeat-related parameters.

150. The apparatus according to claim 148, wherein the control unit is adapted to:

determine at least one breathing pattern of the subject responsively to the sensed breathing-related parameter,

compare the breathing pattern with a baseline breathing pattern, and

predict the onset at least in part responsively to the comparison.

151. The apparatus according to claim 139, wherein the sensor comprises a pressure gauge, configured to measure a pressure in, on, or under a reclining surface upon which the subject lies.

152. The apparatus according to claim 151, wherein the pressure gauge comprises exactly one pressure gauge.

153. Apparatus for predicting an onset of an episode associated with congestive heart failure (CHF), comprising:

a non-contact sensor, adapted to sense at least one parameter of a subject without contacting the subject or clothes the subject is wearing; and

a control unit, adapted to predict the onset of the episode at least in part responsively to the sensed parameter.

154. The apparatus according to claim 153, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein the sensor is adapted to sense the at least one motion-related parameter.

155. The apparatus according to claim 153, wherein the sensor comprises a pressure gauge, configured to measure a pressure in, on, or under a reclining surface upon which the subject lies.

156. The apparatus according to claim 153, wherein the sensor is adapted to sense the at least one parameter while the subject is sleeping.

157. The apparatus according to claim 153, wherein the sensor is adapted to sense a breathing-related parameter of the subject, and a blood pressure of the subject, and wherein the control unit is adapted to predict the onset at least in part responsively to the breathing-related parameter and the blood pressure.

158. The apparatus according to claim 153, wherein the sensor is adapted to sense the at least one parameter without requiring human compliance.

159-164. -164. (canceled)

165. Apparatus for predicting an onset of a clinical episode, comprising:

a sensor, adapted to sense at least one parameter of a subject without requiring human compliance; and

a control unit, adapted to predict the onset at least in part responsively to the sensed parameter.

166. The apparatus according to claim 165, wherein the sensor comprises a non-contact sensor, adapted to sense the at least one parameter without contacting the subject or clothes the subject is wearing.

167. The apparatus according to claim 165, wherein the at least one parameter includes at least one motion-related parameter of the subject, and wherein the sensor is adapted to sense the at least one motion-related parameter without requiring human compliance.

168. The apparatus according to claim 165, wherein the sensor is adapted to sense the at least one parameter while the subject is sleeping, and comprising a user interface, wherein the control unit is adapted to drive the user interface to alert the subject to the predicted onset only after the subject awakes.

169. The apparatus according to claim 165, wherein the sensor comprises a pressure gauge, configured to measure a pressure in, on, or under a reclining surface upon which the subject lies.

170. The apparatus according to claim 165, wherein the clinical episode includes an asthma attack, and wherein the control unit is adapted to predict the onset of the asthma attack.

171. The apparatus according to claim 165, wherein the clinical episode includes an episode associated with congestive heart failure (CHF) of the subject, and wherein the control unit is adapted to predict the onset of the episode associated with the CHF.

172. The apparatus according to claim 165, wherein the clinical episode includes an episode of hypoglycemia caused by diabetes, and wherein the control unit is adapted to predict the onset of the episode of hypoglycemia.

173. The apparatus according to claim 165, wherein the clinical episode is selected from the list consisting of:

an episode of abnormal autonomic nervous system activity caused by a neurological condition, an epileptic seizure, an episode of Periodic Limb Movements in Sleep (PLMS), a stroke, an episode of essential tremor, an episode of stress, an episode of fibrillation, an episode associated with chronic obstructive pulmonary disease (COPD), an episode associated with cystic fibrosis (CF), and an episode of anaphylactic shock, and wherein the control unit is adapted to predict the onset of the selected clinical episode.

174. The apparatus according to claim 165, wherein the at least one parameter includes at least one breathing-related parameter of the subject, and wherein the sensor is adapted to sense the at least one breathing-related parameter without requiring human compliance.

175. The apparatus according to claim 174, wherein the control unit is adapted to:

determine at least one breathing pattern of the subject responsively to the sensed breathing-related parameter,

compare the breathing pattern with a baseline breathing pattern, and

predict the onset at least in part responsively to the comparison.