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1. WO2020198730 - SYSTÈME DE SURVEILLANCE DE PATIENT

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CLAIMS

What is claimed is:

1. A sensor module for patient monitoring, the sensor module comprising:

a processor circuitry;

a memory circuitry;

at least one time of flight (TOF) sensor;

a TOF logic configured to determine a sequence of elevation maps of at least a portion of a patient room, the TOF logic further configured to determine at least one of a distance vector and a velocity vector associated with a selected room occupant based, at least in part, on a plurality of elevation maps in the sequence of elevation maps, each elevation map determined based, at least in part, on a respective TOF data set captured from the at least one TOF sensor, each TOF data set captured, periodically, at a time interval; and

a monitor logic configured to classify an activity of the selected room occupant as acceptable or unacceptable, the classifying based, at least in part, on the at least one of the distance vector and the velocity vector.

2. The sensor module of claim 1, wherein the monitor logic is configured to notify a facility management system if the classification corresponds to unacceptable, or log the activity of the selected room occupant if the classification corresponds to acceptable.

3. The sensor module of claim 1, wherein the TOF logic is configured to determine whether the patient room is occupied based, at least in part, on a baseline elevation map.

4. The sensor module according to any one of claims 1 through 3, wherein the monitor logic is trained using a machine learning technique.

5. The sensor module according to any one of claims 1 through 3, wherein the TOF data set is captured from a plurality of TOF sensors.

6. The sensor module according to any one of claims 1 through 3, wherein the monitor logic is configured to receive TOF data from a secondary sensor module.

7. A method comprising:

determining, by a time of flight (TOF) logic, a sequence of elevation maps of at least a portion of a patient room, each elevation map determined based, at least in part, on a

respective TOF data set captured from at least one TOF sensor, each TOF data set captured, periodically, at a time interval;

determining, by the TOF logic, at least one of a distance vector and a velocity vector associated with a selected room occupant based, at least in part, on a plurality of elevation maps in the sequence of elevation maps; and

classifying, by a monitor logic, an activity of the selected room occupant as acceptable or unacceptable, the classifying based, at least in part, on the at least one of the distance vector and the velocity vector.

8. The method of claim 7, further comprising notifying, by the monitor logic, a facility management system if the classification corresponds to unacceptable or logging by the monitor logic, the activity of the selected room occupant if the classification corresponds to acceptable.

9. The method of claim 7, further comprising determining, by the TOF logic, whether the patient room is occupied based, at least in part, on a baseline elevation map.

10. The method of claim 7, wherein the monitor logic is trained using a machine learning technique.

11. The method of claim 7, wherein the TOF data set is captured from a plurality of TOF sensors.

12. The method of claim 11, wherein the plurality of TOF sensors is included in a single sensor module.

13. The method of claim 7, further comprising determining, by the monitor logic, a number of room occupants based, at least in part, on a selected elevation map and classifying the number of room occupants as acceptable or unacceptable based, at least in part, on a policy.

14. A patient monitoring system, the system comprising:

a primary sensor module; and

at least one secondary sensor module coupled to the primary sensor module, the primary sensor module comprising:

a processor circuitry,

a memory circuitry,

at least one time of flight (TOF) sensor,

a TOF logic configured to determine a sequence of elevation maps of at least a portion of a patient room, the TOF logic further configured to determine at least one of a distance vector and a velocity vector associated with a selected room occupant based, at least in part, on a plurality of elevation maps in the sequence of elevation maps, each elevation map determined based, at least in part, on a respective TOF data set captured from the at least one TOF sensor, each TOF data set captured, periodically, at a time interval, and

a monitor logic configured to classify an activity of the selected room occupant as acceptable or unacceptable, the classifying based, at least in part, on the at least one of the distance vector and the velocity vector.

15. The system of claim 14, wherein the monitor logic is configured to notify a facility management system if the classification corresponds to unacceptable, or log the activity of the selected room occupant if the classification corresponds to acceptable.

16. The system of claim 14, wherein the TOF logic is configured to determine whether the patient room is occupied based, at least in part, on a baseline elevation map.

17. The system according to any one of claims 14 through 16, wherein the monitor logic is trained using a machine learning technique.

18. The system according to any one of claims 14 through 16, wherein the TOF data set is captured from a plurality of TOF sensors.

19. The system according to any one of claims 14 through 16, wherein the monitor logic is configured to receive TOF data from each secondary sensor module.

20. A computer readable storage device having stored thereon instructions that when executed by one or more processors result in the following operations comprising: the method according to any one of claims 7 through 13.