Granted Patent B2

US 12,640,244 · App. 18/233,992 · Granted May 26, 2026

Inventors: Jenny Margarito (Eindhoven, NL); Boris Emmanuel Rachmund De Ruyter (Peer, BE); Jan Martijn Krans (Den Bosch, NL)

Assignee: KONINKLIJKE PHILIPS N.V.

G16H20/00G16H50/20

Abstract

Claims (25)

1 . A therapy management system, comprising:

a processor; and

a memory communicatively coupled to the processor, the memory storing logic that includes a set of instructions executable by the processor, which when executed by the processor, cause the processor to:

automatically extract, via a personality type feature extractor, one or more features describing mobile apps usage based on one or more mobile apps logs from a mobile device associated with a patient receiving obstructive sleep apnea treatment, wherein the features describing mobile apps usage comprise one or more of: usage frequency, usage time, or usage visualized content, browser search terms relating to obstructive sleep apnea, in app interaction data, motion or physical activity information, and characteristics of patient responses during therapy setup including at least response latency, response length, and linguistic tone extracted via natural language processing;

determine, via a personality type detector that comprises a pretrained classification model, a personality type of the patient based on processing the one or more features describing mobile apps usage from the personality type feature extractor utilizing the pretrained classification model, the pretrained classification model having been trained via supervised learning using, as inputs, features extracted from smartphone data and, as labels, personality types obtained from a personality questionnaire;

determine, via an automatic messages generator, a treatment guidance for the patient based on the personality type, wherein the treatment guidance comprises a first set of messages for the patient in response to a first personality type and a second set of messages for the patient in response to a different second personality type,

wherein the second set of messages is different than the first set of messages, and wherein the automatic messages generator modifies one or more of the content, frequency, and timing of the messages based on device usage data from a therapeutic device and patient response data during therapy setup, including comparing perceived usage reported by the patient to actual usage measured by the therapeutic device and updating subsequent messages upon detecting a discrepancy between the perceived usage and the measured usage and based on a measured response latency during therapy setup; and

communicate, via the automatic messages generator, the treatment guidance for the patient to the mobile device associated with the patient receiving obstructive sleep apnea treatment.

2 . The therapy management system of claim 1 , wherein the set of instructions, which when executed by the processor, cause the processor further to: receive, via the personality type feature extractor, one or more mobile apps logs of one or more mobile apps from the mobile device; receive, via the personality type detector, the features describing mobile apps usage from the personality type feature extractor; and receive, via the automatic messages generator, the personality type of the patient from the personality type detector.

3 . The therapy management system of claim 1 , wherein the operation to determine the treatment guidance comprises determination of one or more of a first content, a first frequency, or a first timing associated with the first set of messages in response to the first personality type and one or more of a different second content, a different second frequency, or a different second timing associated with the different second set of messages in response to the different second personality type.

4 . The therapy management system of claim 3 , wherein the set of instructions, which when executed by the processor, cause the processor further to: receive, via the automatic messages generator, device usage data from a therapeutic device; and modify, via the automatic messages generator, the treatment guidance based on the device usage data, wherein the operation to modify the treatment guidance comprises modification of one or more of the first content, the first frequency, or the first timing associated with the first set of messages in response to the first personality type and one or more of the different second content, the different second frequency, or the different second timing associated with the different second set of messages in response to the different second personality type based on the device usage data.

5 . The therapy management system of claim 3 , wherein the set of instructions, which when executed by the processor, cause the processor further to: receive, via the automatic messages generator, patient response data from one or more of the therapeutic device or the mobile device; and modify, via the automatic messages generator, the treatment guidance based on the patient response data, wherein the patient response data is based on patient responses during therapy set-up of the obstructive sleep apnea treatment, wherein the operation to modify the treatment guidance comprises modification of one or more of the first content, the first frequency, or the first timing associated with the first set of messages in response to the first personality type and one or more of the different second content, the different second frequency, or the different second timing associated with the different second set of messages in response to the different second personality type based on the patient response data.

6 . A non-transitory computer readable medium, having stored thereon a set of instructions, which when executed by a computing device, cause the computing device to: automatically extract, via a personality type feature extractor, one or more features describing mobile apps usage based on one or more mobile apps logs from a mobile device associated with a patient receiving obstructive sleep apnea treatment, wherein the features describing mobile apps usage comprise one or more of: usage frequency, usage time, or usage visualized content, browser search terms relating to obstructive sleep apnea, in app interaction data, motion or physical activity information, and characteristics of patient responses during therapy setup including at least response latency, response length, and linguistic tone extracted via natural language processing; determine, via a personality type detector that comprises a pretrained classification model, a personality type of the patient based on processing the one or more features describing mobile apps usage from the personality type feature extractor utilizing the pretrained classification model, the pretrained classification model having been trained via supervised learning using, as inputs, features extracted from smartphone data and, as labels, personality types obtained from a personality questionnaire; determine, via an automatic messages generator, a treatment guidance for the patient based on the personality type, wherein the treatment guidance comprises a first set of messages for the patient in response to a first personality type and a second set of messages for the patient in response to a different second personality type,

wherein the second set of messages is different than the first set of messages, and wherein the automatic messages generator modifies one or more of the content, frequency, and timing of the messages based on device usage data from a therapeutic device and patient response data during therapy setup, including comparing perceived usage reported by the patient to actual usage measured by the therapeutic device and updating subsequent messages upon detecting a discrepancy between the perceived usage and the measured usage and based on a measured response latency during therapy setup; and

communicate, via the automatic messages generator, the treatment guidance for the patient to the mobile device associated with the patient receiving obstructive sleep apnea treatment.

7 . The non-transitory computer readable medium of claim 6 , wherein the set of instructions, which when executed by the computing device, cause the computing device further to: receive, via the personality type feature extractor, one or more mobile apps logs of one or more mobile apps from the mobile device; receive, via the personality type detector, the features describing mobile apps usage from the personality type feature extractor; and receive, via the automatic messages generator, the personality type of the patient from the personality type detector.

8 . The non-transitory computer readable medium of claim 6 , wherein the operation to determine the treatment guidance comprises determination of one or more of a first content, a first frequency, or a first timing associated with the first set of messages in response to the first personality type and one or more of a different second content, a different second frequency, or a different second timing associated with the different second set of messages in response to the different second personality type.

9 . The non-transitory computer readable medium of claim 8 , wherein the set of instructions, which when executed by the computing device, cause the computing device further to: receive, via the automatic messages generator, device usage data from a therapeutic device; and modify, via the automatic messages generator, the treatment guidance based on the device usage data, wherein the operation to modify the treatment guidance comprises modification of one or more of the first content, the first frequency, or the first timing associated with the first set of messages in response to the first personality type and one or more of the different second content, the different second frequency, or the different second timing associated with the different second set of messages in response to the different second personality type based on the device usage data.

10 . The non-transitory computer readable medium of claim 8 , wherein the set of instructions, which when executed by the computing device, cause the computing device further to: receive, via the automatic messages generator, patient response data from one or more of the therapeutic device or the mobile device; and modify, via the automatic messages generator, the treatment guidance based on the patient response data, wherein the patient response data is based on patient responses during therapy set-up of the obstructive sleep apnea treatment, wherein the operation to modify the treatment guidance comprises modification of one or more of the first content, the first frequency, or the first timing associated with the first set of messages in response to the first personality type and one or more of the different second content, the different second frequency, or the different second timing associated with the different second set of messages in response to the different second personality type based on the patient response data.

11 . A therapy management method, comprising: automatically extracting via a personality type feature extractor, one or more features describing mobile apps usage based on one or more mobile apps logs from a mobile device associated with a patient receiving obstructive sleep apnea treatment, wherein the features describing mobile apps usage comprise one or more of: usage frequency, usage time, or usage visualized content, browser search terms relating to obstructive sleep apnea, in app interaction data, motion or physical activity information, and characteristics of patient responses during therapy setup including at least response latency, response length, and linguistic tone extracted via natural language processing; determining, via a personality type detector that comprises a pretrained classification model, a personality type of the patient based on processing the one or more features describing mobile apps usage from the personality type feature extractor utilizing the pretrained classification model, the pretrained classification model having been trained via supervised learning using, as inputs, features extracted from smartphone data and, as labels, personality types obtained from a personality questionnaire; determining, via an automatic messages generator, a treatment guidance for the patient based on the personality type, wherein the treatment guidance comprises a first set of messages for the patient in response to a first personality type and a second set of messages for the patient in response to a different second personality type,

wherein the second set of messages is different than the first set of messages, and wherein the automatic messages generator modifies one or more of the content, frequency, and timing of the messages based on device usage data from a therapeutic device and patient response data during therapy setup, including comparing perceived usage reported by the patient to actual usage measured by the therapeutic device and updating subsequent messages upon detecting a discrepancy between the perceived usage and the measured usage and based on a measured response latency during therapy setup; and

communicating, via the automatic messages generator, the treatment guidance for the patient to the mobile device associated with the patient receiving obstructive sleep apnea treatment.

12 . The therapy management method of claim 11 , wherein the operation to determine the treatment guidance comprises determination of one or more of a first content, a first frequency, or a first timing associated with the first set of messages in response to the first personality type and one or more of a different second content, a different second frequency, or a different second timing associated with the different second set of messages in response to the different second personality type.

13 . The therapy management method of claim 12 , further comprising: receiving, via the automatic messages generator, device usage data from a therapeutic device; and modifying, via the automatic messages generator, the treatment guidance based on the device usage data, wherein the operation to modify the treatment guidance comprises modification of one or more of the first content, the first frequency, or the first timing associated with the first set of messages in response to the first personality type and one or more of the different second content, the different second frequency, or the different second timing associated with the different second set of messages in response to the different second personality type based on the device usage data.

14 . The therapy management method of claim 12 , further comprising: receiving, via the automatic messages generator, patient response data from one or more of a therapeutic device or the mobile device; and modifying, via the automatic messages generator, the treatment guidance based on the patient response data, wherein the patient response data is based on patient responses during therapy set-up of the obstructive sleep apnea treatment, wherein the operation to modify the treatment guidance comprises modification of one or more of the first content, the first frequency, or the first timing associated with the first set of messages in response to the first personality type and one or more of the different second content, the different second frequency, or the different second timing associated with the different second set of messages in response to the different second personality type based on the patient response data.

Assignments (1)

Priority Claims (1)

Continuity (1)

References Cited (24)