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WO2016142734A1 - Système de télémédecine utilisant un dispositif d'acquisition multicapteur - Google Patents

Système de télémédecine utilisant un dispositif d'acquisition multicapteur Download PDF

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Publication number
WO2016142734A1
WO2016142734A1 PCT/IB2015/000944 IB2015000944W WO2016142734A1 WO 2016142734 A1 WO2016142734 A1 WO 2016142734A1 IB 2015000944 W IB2015000944 W IB 2015000944W WO 2016142734 A1 WO2016142734 A1 WO 2016142734A1
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Prior art keywords
sensor
living
information
processing module
physiological feature
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PCT/IB2015/000944
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English (en)
Inventor
Eric Thibaut
Jean-Yves GAUVRIT
Thierry Moudenc
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Mis tic
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Mis tic
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Priority to PCT/IB2015/000944 priority Critical patent/WO2016142734A1/fr
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
    • A61B5/0022—Monitoring a patient using a global network, e.g. telephone networks, internet
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/08—Measuring devices for evaluating the respiratory organs
    • A61B5/0816—Measuring devices for examining respiratory frequency
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation

Definitions

  • the present invention concerns a telemedicine system and a method for remotely obtaining a physiological feature of a living being.
  • Medical devices helping a doctor to make a diagnosis have substantially evolved during the last decades. Indeed, medical devices, such as radiographic devices, echography devices, ophthalmologic devices, etc. have become more user-friendly with a reduction of their size, their weight and an improvement of their user interface.
  • Telemedicine is a solution often evocated to avoid displacing a doctor.
  • Telemedicine capable devices are slow. Several reasons may explain this situation.
  • the invention concerns a telemedicine system for remotely obtaining a physiological feature of a living being
  • the system comprises: an acquisition system comprising an multi sensor device provided with at least a first sensor and a second sensor, each sensor being adapted to provide a sensor signal comprising information relative to the living being; a processing module for processing sensor signals, said processing module comprising: extraction means for extracting first information representative of a searched physiological feature of a living being from a first sensor signal; search means for searching second information representative of the searched physiological feature in at least one second sensor signal; and, identification means for identifying a physiological feature in function of the first information and a second information correlated to the first information; a client system comprising a display device for displaying data representative of identified physiological features received from the processing module, the acquisition system and the client system being positioned at different geographical positions.
  • the telemedicine system of the invention is particularly efficient in the detection of physiological features, since each identification is based on a collaboration between a plurality of different sensors that can be used to detect and confirm a detection of a physiological feature.
  • the processing module comprises a derivation means adapted to derive a signal representative of a living being from a sensor signal, each sensor signal used by the extraction means and the search means being a signal resulting from a pre-processing by the derivation means.
  • a derivation means allows concentrating the search of physiological features on a signal representing quasi exclusively the living being.
  • the processing module is positioned at a geographical position different from the geographical position of the acquisition system and/or different from the geographical position of the client system, the processing module comprising communication means for communicating with the acquisition system and/or the client system when the acquisition system and/or the client system are positioned at a different geographical position.
  • At least two of the means comprised in the processing module are located at different geographical positions, means of the processing module located at different geographical positions being associated to communications means to communicate with the other means of the processing module and/or the acquisition system and/or the client system.
  • the systems, modules and means of the telemedicine system located at a same geographical position are comprised in a same integrated apparatus.
  • the processing module comprises object detection means adapted to detect at least a part of a living being and to provide information representative of the living being to the derivation means to allow the derivation means to derive the signal representative of a living being from a sensor signal.
  • the object detection means use infra-red images, comprising at least a part of a living being, provided by a thermal sensor.
  • the first sensor is an image sensor providing images in a visible domain and the second sensor comprises an audio sensor providing audio signals and/or a thermal sensor providing infra-red images
  • the extraction means being adapted to extract first information representative of movements of the living being from images provided by the image sensor
  • the search means being adapted to search second information representative of a respiratory frequency of the living being from an audio signal provided by the audio sensor and/or the search means being adapted to search second information representative of a temperature of the living being from infra-red images provided by the thermal sensor
  • the identification means searching an increase of respiratory frequencies and/or an increase of temperatures of the living being correlated with an increase of movements of the living being to identify a physiological feature.
  • the processing module comprises storage means for storing a reference physiological feature and determination means for determining an evolution over time of physiological features of the living being with respect to the reference physiological feature, the information representative of identified physiological features displayed on the display device being an information representative of the evolution over time of physiological features of the living being.
  • the processing module has access to a database comprising data representative of known physiological features, the processing module being adapted to use said database to represent on the display device an information representative of a difference between the data representative of identified physiological features and the data representative of a known physiological feature.
  • the client system comprises means to send a request to modify a parameterization of at least one of the sensor of the multi-sensor device either before any acquisition of a sensor signal or after display of the data representative of identified physiological features, to obtain additional information on the identified physiological feature or to increase a precision of the identified physiological feature.
  • the invention concerns a method for remotely obtaining a physiological feature of a living being wherein the method comprises: using a plurality of sensors for acquiring a plurality of sensor signals comprising information relative to the living being; extracting first information representative of a searched physiological feature of a living being from a first sensor signal; searching second information representative of the searched physiological feature of the living in at least one second sensor signal; identifying a physiological feature in function of the first information and second information correlated to the first information; displaying on a display device, data representative of identified physiological features, the plurality of sensors and the display device being positioned at different geographical positions.
  • the invention concerns a computer program characterized in that it comprises program code instructions which can be loaded in a programmable device for implementing the method according to the second aspect, when the program code instructions are run by the programmable device.
  • the invention concerns information storage means storing a computer program comprising program code instructions which can be loaded in a programmable device for implementing the method according to the second aspect, when the program code instructions are run by the programmable device.
  • FIG. 1 illustrates schematically an example of a telemedicine system allowing to remotely obtain physiological features of a living being
  • FIG. 2A illustrates schematically an example of an acquisition system comprising an acquisition device provided with a plurality of sensors
  • FIG. 2B illustrates schematically an example of a client system comprising a display device for displaying data representative of physiological features
  • FIG. 3 illustrates schematically an example of a hardware architecture of a processing module comprised in an acquisition system comprised in the telemedicine system;
  • - Fig. 4 illustrates schematically an example of a hardware architecture of a processing module comprised in a client system comprised in the telemedicine system
  • - Fig. 5 illustrates schematically a first example of a method implemented by the telemedicine system allowing to remotely obtain physiological features of a living being
  • FIG. 6 illustrates schematically a second example of a method implemented by the telemedicine system allowing to remotely obtain physiological features of a living being.
  • the description below describes several embodiments of the invention focusing on a system adapted to remotely obtain a physiological feature of a human being.
  • the principles of the invention can be adapted however to a broader context, and for instance to a system adapted to remotely obtain a physiological feature of any living being, or of a group of living beings.
  • a system adapted to detect physiological features corresponding to neurological diseases such as Parkinson's disease, Alzheimer disease, tachycardia or epilepsy.
  • the principle of the invention can be adapted to other diseases for which physiological features can be captured by a plurality of sensors.
  • Fig. 1 illustrates schematically an example of a telemedicine system allowing to remotely obtain physiological features of a living being.
  • an acquisition system 10 communicates with a client system 1 1 via a communication network 12.
  • the acquisition system 10 is installed in a first room in which a patient 13 stays.
  • the client system is installed in a second room in which a doctor 14 works.
  • the first and the second rooms are located in different geographical positions.
  • the client system 1 1 comprises a display device on which are displayed information representative of physiological features of the patient 13 and/or information representative of evolutions of physiological features of the patient 13. These information are used by the doctor 14 to pronounce a diagnosis.
  • the acquisition system 10 comprises a multi-sensor device provided with a plurality of sensors. Each sensor of the plurality of sensors is focused on the patient 13.
  • Fig. 2 A illustrates schematically an example of an acquisition system 10 comprising a multi-sensor device provided with a plurality of sensors, said acquisition system 10 being used in the telemedicine system.
  • the acquisition system 10 comprises a multi-sensor device provided with a plurality of sensors. Each sensor is adapted to provide a sensor signal comprising information relative to the patient 13.
  • Fig. 1 illustrates schematically an example of an acquisition system 10 comprising a multi-sensor device provided with a plurality of sensors, said acquisition system 10 being used in the telemedicine system.
  • the acquisition system 10 comprises a multi-sensor device provided with a plurality of sensors. Each sensor is adapted to provide a sensor signal comprising information relative to the patient 13.
  • Fig. 2 A illustrates schematically an example of an acquisition system 10 comprising a multi-sensor device provided with a plurality of sensors, said acquisition system 10 being used in the telemedicine system.
  • the acquisition system 10 comprises a multi-sensor device provided with a plurality of sensors. Each sensor is adapted to provide a
  • the multi-sensor device comprises a thermal sensor 101 adapted to capture sequences of images in an infra-red domain (called “infra-red images” in the following) in which a colour of a pixel depends on the temperature of an object comprising the pixel, a high definition (HD) sensor 102 adapted to capture sequences of images in a visible domain (called “HD images” in the following), and a microphone 103 adapted to capture an audio signal.
  • infra-red images in which a colour of a pixel depends on the temperature of an object comprising the pixel
  • HD images high definition
  • the acquisition system 10 comprises a processing module 105 described in more details in relation with Fig. 3.
  • the processing module 105 is adapted to perform various processing.
  • the processing module 105 is adapted to control the plurality of sensors comprised in the acquisition device. In an embodiment, all sensors are started and stopped at the same time in order to obtain sequences of images and audio signals corresponding to a same period of acquisition.
  • the processing module is also adapted to apply data compression algorithms to each sensor signal. For instance, sequences of infra-red images provided by the thermal sensor 101 and sequences of HD images provided by the HD sensor 102 are compressed in a H264/AVC format (ISO/IEC 14496-10 - MPEG-4 Part 10, Advanced Video Coding / ITU-T H.264) or in the emerging format HEVC (ISO/IEC 23008-2 - MPEG-H Part 2, High Efficiency Video Coding / ITU-T H.265).
  • the audio signal provided by the microphone 103 is, for example, compressed in an AAC format (Advanced Audio Coding, ISO/IEC 14496-3).
  • the processing module 105 is adapted to insert each compressed sensor signal in a transport stream such as, for instance, a MPEG Transport Stream (MPEG TS: ISO/IEC 13818-1) in which it is associated to time information corresponding to the period of acquisition of the sensor signal.
  • MPEG Transport Stream MPEG TS: ISO/IEC 13818-1
  • the acquisition system 10 comprises a communication device 104 such as, for instance, a radio communication device or an Ethernet communication device.
  • the communication device is adapted to transmit to the client system 1 1, the transport stream containing the compressed sensor signals.
  • the sensors, the module and the device of the acquisition system 10 communicate using a communication bus 100.
  • Non-invasive sensors doesn't need to touch a patient to obtain a sensor signal while an invasive sensor needs to touch the patient at least one time to obtain a sensor signal.
  • Non-invasive sensors comprise, the HD sensor, the thermal sensor and the microphone already mentioned but also for example, X ray sensors, sensors adapted to measure an electromagnetic fields, electrochemical sensors, etc.
  • Invasive sensors comprises, for example, echography sensors, endoscope, etc.
  • Fig. 2B illustrates schematically an example of a client system 11 comprising a display device 113 for displaying data representative of physiological features.
  • the display device 113 could be a smartphone, a touch pad, a display of a computer, a video projector, an optical head-mounted display such as electronic glasses, and devices with augmented reality capabilities.
  • the client system 11 comprises a communication device 111 such as, for instance, a radio communication device or an Ethernet communication device.
  • the communication device 111 is adapted to receive, from the acquisition system 10, transport streams containing compressed sensor signals.
  • the client system 11 comprises a processing module 112 adapted to extract the compressed sensor signals from the transport stream, and to decompress each compressed sensor signal.
  • the processing module implements a method allowing to obtain physiological features of a living being from the sensor signals. Two examples of methods allowing to obtain physiological features of a living being from the sensor signals are described in the following in relation with Figs. 5 and 6. Obtained physiological features are then displayed on a display device 1 13 comprised in the client system 11.
  • the module and the devices of the client system 1 1 communicate using a communication bus 110.
  • Fig. 3 illustrates schematically an example of a hardware architecture of the processing module 105 comprised in the telemedicine system.
  • the processing module 105 comprises the following components interconnected by a communications bus 1055: a processor, microprocessor, microcontroller or CPU ⁇ Central Processing Unit) 1050; a RAM ⁇ Random-Access Memory) 1051; a ROM ⁇ Read-Only Memory) 1052; storage means such as a HDD ⁇ Hard-Disk Drive) 1053, or any other device adapted to read information stored by storage means; and a communication interface 1054.
  • a communications bus 1055 a processor, microprocessor, microcontroller or CPU ⁇ Central Processing Unit) 1050; a RAM ⁇ Random-Access Memory) 1051; a ROM ⁇ Read-Only Memory) 1052; storage means such as a HDD ⁇ Hard-Disk Drive) 1053, or any other device adapted to read information stored by storage means; and a communication interface 1054.
  • the communication interface 1054 allows the processing module 105 to receive sensor signals from the infra-red sensor 101, the HD sensor 102 and the microphone 103 via the communication bus 100.
  • CPU 1050 is capable of executing instructions loaded into RAM 1051 from ROM 1052 or from an external memory, such as an SD card or the HDD 1053. After the processing module 105 has been powered on, CPU 1050 is capable of reading instructions from RAM 1051 and executing these instructions.
  • the instructions form one computer program that causes CPU 1050 to perform the control of the sensors, the compression of the sensor signals and the insertion of the compressed sensor signals in a transport stream.
  • the control of the sensors and/or the compression of the sensor signal and/or the insertion of the compressed sensor signals in a transport stream may be implemented in software by execution of a set of instructions or program by a programmable computing machine, such as a PC ⁇ Personal Computer), a DSP ⁇ Digital Signal Processor) or a microcontroller; or else implemented in hardware by a machine or a dedicated component, such as an FPGA ⁇ Field-Programmable Gate Array) or an ASIC ⁇ Application-Specific Integrated Circuit).
  • a programmable computing machine such as a PC ⁇ Personal Computer
  • DSP Digital Signal Processor
  • microcontroller or else implemented in hardware by a machine or a dedicated component, such as an FPGA ⁇ Field-Programmable Gate Array) or an ASIC ⁇ Application-Specific Integrated Circuit.
  • Fig. 4 illustrates schematically an example of a hardware architecture of the processing module 112 comprised in the telemedicine system.
  • the processing module 112 comprises the following components interconnected by a communications bus 1125: a processor, microprocessor, microcontroller or CPU ⁇ Central Processing Unit) 1120; a RAM ⁇ Random-Access Memory) 1121; a ROM ⁇ Read-Only Memory) 1122; storage means such as HDD ⁇ Hard-Disk Drive) 1123, or any other device adapted to read information stored by storage means; and a communication interface 1124.
  • the communication interface 1124 allows the processing module 112 to receive compressed sensor signals from the communication device 11 1 and to transmit information representative of physiological features to the display device 113 via the communication bus 110.
  • CPU 1120 is capable of executing instructions loaded into RAM 1121 from ROM 1122 or from an external memory, such as an SD card or the HDD 1123. After the processing module 112 has been powered on, CPU 1120 is capable of reading instructions from RAM 1121 and executing these instructions.
  • the instructions form one computer program that causes CPU 1120 to perform the extraction of compressed sensor signals from a received transport stream, the decompression of the compressed sensor signals, the transmission of the information representative of the physiological features to the display device 1 13, and the determination of physiological features of a living being from the sensor signals using, for example, one of the method described in relation with Figs 5 and 6.
  • the extraction of compressed sensor signals from a received transport stream, the decompression of the compressed sensor signals, the transmission of information representative of the physiological features to the display device 113, and any or all steps of the methods described in relation with Figs 5 and 6 may be implemented in software by execution of a set of instructions or program by a programmable computing machine, such as a PC ⁇ Personal Computer), a DSP ⁇ Digital Signal Processor) or a microcontroller; or else implemented in hardware by a machine or a dedicated component, such as an FPGA ⁇ Field-Programmable Gate Array) or an ASIC ⁇ Application-Specific Integrated Circuit).
  • a programmable computing machine such as a PC ⁇ Personal Computer
  • DSP Digital Signal Processor
  • microcontroller or else implemented in hardware by a machine or a dedicated component, such as an FPGA ⁇ Field-Programmable Gate Array) or an ASIC ⁇ Application-Specific Integrated Circuit.
  • Fig. 5 illustrates schematically a first example of a method implemented by the telemedicine system allowing to remotely obtain physiological features of a living being.
  • the processing module 105 of the acquisition system 10 controls the thermal sensor 101, the HD sensor 102 and the microphone 103 to start an acquisition of sensor signals on a predefined period, called acquisition period, comprising respectively a sequence of infra-red images, a sequence of HD images and an audio sequence.
  • acquisition period a predefined period
  • Each sensor signal comprises information relative to the patient 13.
  • the processing module 105 compresses each sensor signal and inserts the obtained compressed sensor signals in a transport stream.
  • the processing module 105 then transmits the obtained transport stream to the communication device 104 that transmits the transport stream to the client device 11.
  • the communication device 1 11 of the client system 11 receives the transmitted transport stream and forwards this transport stream to the processing module 112.
  • the processing module 112 extracts the compressed sensor signals from the transport stream and decompresses each compressed sensor signal.
  • the processing module 112 starts by extracting first information representative of a searched physiological feature of the patient 13 from the sequence of HD images.
  • the telemedicine system searches for a physiological feature related to a neurological disease such as Parkinson's disease, Alzheimer disease, epilepsy.
  • a characteristic of a patient suffering of such neurological disease is to present uncontrolled movements. These uncontrolled movements have generally a low amplitude but are regular. The movement of a patient is therefore an information that could be representative of the searched neurological disease.
  • Movements of a patient can be detected in images in the form of image motion. If it is considered here that the patient 13 is the only entity that can move in an image acquired by the HD sensor 102, it is possible to detect uncontrolled movements of a patient by analyzing the motion in the sequence of HD images.
  • the processing module 112 computes a difference between each pair of successive HD images of the sequence of HD images. Each difference could be computed as the sum of absolute differences between each pair of pixels located at the same spatial position in two HD images of a pair of consecutive HD images. Each computed difference extracted on the sequence of HD images is then considered as a motion information representative of the motion of the patient 13. Motion information extracted from the sequence of HD images are then stored in the storage means 1123.
  • a movement of a patient is not necessarily representative of a physiological feature related to a neurological disease. Consequently, the fact that the movement is due to a neurological disease needs to be confirmed by other means. It is known that a movement due to a neurological disease is associated to an increase of the temperature of a patient and to an increase of the respiratory frequency of the patient that can start few minutes before the start of the uncontrolled movement of a patient. These information could be used to confirm that the movements of a patient are a physiological feature of the patient related to a neurological disease such as Parkinson's disease, Alzheimer disease or epilepsy.
  • the processing module 112 searches in the audio signal and the sequence of infra-red images second information representative of the searched physiological feature correlated to the first information.
  • the processing module 112 searches first to determine the respiratory frequency of a patient. It is considered here that the patient is the only entity that had produced a sound during the period of acquisition.
  • the audio signal is then analysed to determine parts of the audio signal corresponding to sounds with low amplitude and parts of the audio signal corresponding to sounds with high amplitude. Sounds with low amplitude are considered as silence. Sounds with high amplitude are considered as a breathing.
  • the acquisition period is then divided in a succession of sub periods of few minutes.
  • the respiratory frequency is then determined during each sub period by dividing the number of breathing during the duration of the sub period. Respiratory frequencies are then stored in the storage means 1123.
  • the processing module 112 searches then to determine the temperature of the patient 13 during the acquisition period.
  • An infra-red image provided by a thermal sensor contains pixels having a colour depending of the temperature of the object containing the pixel. It is considered here that the hottest pixels in infra-red images captured by the thermal sensor 101 correspond to the patient 13 and that the temperature of other objects in the infra-red images is sufficiently lower than the temperature of the patient 13 to allow an accurate differentiation between the patient 13 and other objects. In addition, it is considered that each possible pixel colour value is associated to a known temperature value.
  • the average temperature of a patient is obtained by determining a number of pixels of an infra-red image having a temperature above a given temperature threshold, computing a sum of temperatures of pixels of the infra-red image having a temperature above the given temperature threshold and dividing said sum by the determined number of pixels having a temperature above the given temperature threshold.
  • a temperature threshold could be for example "35°c”.
  • the processing module 1 12 determines the temperature of the patient 13 in each infra-red image of the sequence of infra-red images. Each temperature of the patient 13 is then stored in the storage means 1123.
  • the processing module 112 identifies a physiological feature of the patient 13 in function of first information and second information correlated with the first information. To that end, the processing module 112 searches in the motion information stored in the storage means 1 123, at least one sub period of the acquisition period, called movement period, corresponding to an increase of the movement of the patient 13.
  • a movement period is, for example, a period during which the differences between consecutive images are above a threshold or above an average of the differences between two consecutive images computed on the acquisition period.
  • the processing module 112 searches in the respiratory frequencies stored in the storage means 1123, if an increase of the patient 13 respiratory frequency correlated with the movement period can be identified.
  • the processing module 1 12 uses the respiratory frequencies stored in the storage means 1123 to determine if an increase of the respiratory frequency of the patient 13 has occurred during a period starting few minutes before the movement period and continuing during the movement period.
  • the processing module 112 searches in the temperatures stored in the storage means 1123, an increase of the temperature of the patient 13 correlated to the movement period.
  • the processing module 1 12 determines if an increase of the temperature of the patient 13 has occurred during a period starting few minutes before the movement period and continuing during the movement period.
  • the processing module 112 determines that the movement of the patient 13 is a physiological feature related to the searched neurological disease. Otherwise, if no increase of the respiratory frequency or increase of the temperature correlated with the movement period is found, the processing module 112 determines that the movements of the patient 13 are not a physiological feature related to the searched neurological disease.
  • a step 504 information representative of physiological feature identified during the acquisition period are transmitted to the display device 113, so that this information can be displayed.
  • An information representative of an identified physiological feature could be, for example, a frequency of movements of the patient 13 during a movement period corresponding to a physiological feature, an average of the motion information during a movement period corresponding to a physiological feature, an average of the respiratory frequency of the patient 13 during a movement period corresponding to a physiological feature and an average of the temperatures of the patient 13 during a movement period corresponding to a physiological feature.
  • the frequency of movements of the patient 13 during a movement period could be determined as a division of a number of movement changes during the movement period by the duration of the movement period.
  • a movement change could be defined, for example, as a change of movement amplitude above a threshold and/or a change of a movement direction above a threshold.
  • the displayed information representative of each identified physiological feature can then be used by a doctor to remotely diagnose a neurological disease such as Parkinson's disease, Alzheimer disease or epilepsy. If a plurality of physiological features is identified during the acquisition period, the information representative of the identified physiological features could be enriched with additional information representing a frequency of occurrence of the physiological feature during the acquisition period.
  • the frequency of occurrence of the physiological disease could be defined, for example, as the division of the number of occurrences of the physiological disease during the acquisition period by the duration of the acquisition period.
  • step 500 the processing module 105 of the acquisition system 10 starts by activating only one of the sensors of the multi-sensor device to obtain only one first sensor signal.
  • This first sensor signal is then transmitted to the client system 11 to allow the processing module 1 12 of the client system 11 to search first information representative of a searched physiological feature of the patient 13 in the received first sensor signal.
  • the processing module 112 transmits a message to the acquisition system 10 to request the acquisition system 10 to activate the remaining sensors or the multi-sensor device. All sensor signals are then compressed, inserted in a transport stream and transmitted to the client system 11.
  • Step 501 is then followed by steps 502, 503 and 504 already described.
  • Activating all sensors only when an information representative of a searched physiological feature is detected allows reducing a bitrate of data transmitted to the client system 1 1.
  • the HD sensor 102 is activated first.
  • the processing module 112 of the client system 11 transmits a message to the acquisition system 10 to activate the thermal sensor 101 and the microphone 103.
  • the microphone 103 is activated first.
  • the processing module 112 of the client system 11 transmits a message to the acquisition system 10 to activate the thermal sensor 101 and the HD sensor 102.
  • step 504 of display of information representative of a physiological feature is followed by several additional steps.
  • the client 11 sends a request to modify a parameterization of at least one of the sensors of the multi-sensor device. This request could be sent either automatically, under a control of the processing module 112, or after an intervention of the doctor 14.
  • a modification of a parameterization of the HD sensor 102 is requested to focus the HD sensor 102 on an eye of the patient 13 in order to obtain an image of a pupil of the patient 13.
  • HD images representing the pupil of the patient 13 are sent to the client 11.
  • the processing module 112 of the client 11 analyses these images of the pupil to determine an information representative of motions of the pupil (i.e. information representative of pupil dilatations).
  • information representative of the pupil motion are displayed on the display device 113 to complement the information representative of physiological features displayed during step 504.
  • the processing module 112 of the client system 11 have an access to a medical record of the patient 13.
  • Information contained in the medical record of the patient 13 are used to send a request to the multi-sensor device of the acquisition system 10, to modify a parameterization of at least one of the sensors of the multi-sensor device. For example, if it is known from the medical record that a specific disease has already been diagnosed for the patient 13, sensors are parameterized to search other diseases than the specific disease. Conversely, if it is known from the medical record that the patient 13 has a family history for a particular disease, sensors are parameterized for detecting this particular disease.
  • the request could be sent by the client system 1 1 to the acquisition system 10 before step 500, to parameterize the sensors before a first acquisition of sensor signals, or after step 504, to obtain more precise or additional information on a physiological feature after display of first information representative of a physiological feature.
  • This request could be send either automatically, under a control of the processing module 112, or after an intervention of the doctor 14.
  • the processing module 112 of the client system 11 has an access to a database comprising data representative of known physiological features.
  • Each known physiological feature could be, for example, representative of typical pathological profiles.
  • This database could be used by the processing module 112, in step 504, to compute, for each known physiological feature, an information representative of a difference between the data representative of the known physiological feature and the data representative of the identified physiological feature provided by the telemedicine system. Said information representative of the difference is then displayed on the display device 113 of the client system 11. The information representative of the difference could help the doctor 14 to exclude rapidly some hypothesis if the data representative of the identified physiological feature provided by the telemedicine system is too far from the data representative of a known physiological feature of the database.
  • a parameterization of at least one of the sensors is modified in function of the information representative of the differences computed by the processing module 112. If the data representative of a physiological feature identified during step 503 are close to data representative of known physiological features related to pathological profiles for which one of the sensor signal is not relevant, the client system 11 sends a request to deactivate the sensor providing the irrelevant sensor signal. In the same request or in another request, the client system 11 can also transmit a new parameterization of the remaining sensors.
  • the data representative of a physiological feature identified during step 503 are close to data representative of known physiological features related to pathological profiles for which the motion of a patient is not relevant, but the sound from the patient are particularly relevant.
  • the client system 11 sends a request to the acquisition device 10 to deactivate the HD sensor 102 and to modify a parameter related to a sound amplification of the microphone 103.
  • the client system 11 sends a request to activate the deactivated sensor in order to obtain the relevant signal.
  • This embodiment is particularly relevant when the processing module 105 of the acquisition device 10 has not activated all sensors or the multi-sensor signal during step 500. In an example, the processing module 105 has activated only the microphone 103 during step 500. Based on the audio signal only, the processing module 112 of the client system 1 1 has detected data representative of a physiological feature close to data representative of a known physiological feature related to pathological profiles for which the temperature of a patient is relevant. In that case, the client system sends a request to the acquisition system to activate the thermal sensor 101.
  • Fig. 5 is a predictive method since this method is capable of providing information on physiological features representative of an epilepsy or a tachycardia crisis very early at the beginning of a crisis. For instance a small increase, quasi imperceptible for a human being, of a patient motion, of a respiratory frequency and of a patient temperature could be detected allowing a doctor reacting very early during an epilepsy crisis or a tachycardia crisis.
  • Fig. 6 illustrates schematically a second example of a method implemented by the telemedicine system allowing to remotely obtain physiological features of the patient 13.
  • the health status of the patient 13 with respect to the searched neurological disease is followed on a period sufficiently long to obtain an information representative of the evolution of this status.
  • step 600 identical to step
  • the processing module 105 of the acquisition system 10 applies a preliminary treatment to each HD image of the sequence of HD images.
  • This treatment consists in applying an object detection to HD images, wherein the object to detect is the patient 13 or a part of the patient 13.
  • This object detection consists in removing, from an HD image, objects not belonging to the patient 13.
  • the processing module 105 determines for each pixel of an HD image, if it belongs to the patient 13 using an infra-red image, acquired by the thermal sensor 101, corresponding temporally to the HD image.
  • a pixel of the HD image belonging to the patient 13 is a pixel corresponding spatially to a pixel of the infra-red image having a temperature above the predefined temperature threshold.
  • the identification of pixels belonging to the patient 13 allows deriving a signal, i.e. a modified HD image, representative of the patient 13 from the HD image provided by the HD sensor 102. Pixels of the HD image belonging to the patient 13 keep their original value. Pixels of the HD image not belonging to the patient 13 are set to the value zero.
  • the modified HD image corresponds then to a signal representative of the patient 13.
  • the modified HD images are then used by the processing module 105 in place of the original HD images.
  • the use of modified HD images allows obtaining better compression of the HD images, and allows also a better estimation of the movement of the patient.
  • the step 601 is followed by steps 602, 603 and 604 identical respectively to steps 501, 502 and 503.
  • a step 605 the processing module 112 determines if the physiological feature identified in step 604, is the first physiological determined for the patient 13 or not. If the identified physiological feature is the first physiological feature identified for the patient 13, the step 605 is followed by a step 606 in which the information representative of the physiological feature identified in step 604 are stored in the storage means 1123. Said physiological feature is then considered as a reference physiological feature.
  • Step 606 is followed by a step 609 during which, the telemedicine system waits a period Jbefore going back to step 600.
  • the period T could be equal, for example, to twenty four hours.
  • step 605 is followed by step 607, during which the last physiological feature identified during step 605 is compared to the reference physiological feature.
  • the processing module 112 compares information representative of the last physiological feature identified during step 604 with the corresponding information representative of the reference physiological feature. For example, the processing module 112 determines if the frequency of movements of the patient 13 has increased, decreased or is in a steady state, and/or if the average of the amplitude of the motion information related to the patient 13 has increased, decreased or is in a steady state, and/or if the frequency of occurrence of the physiological feature has increased, decreased or is in a steady state.
  • a step 608 information representative of the evolution of the physiological features are transmitted to the display device 113, so that these information can be displayed on the display device 1 13.
  • the displayed information representative of the evolution of the physiological feature of the patient 13 can then be used by a doctor to remotely determine an evolution of the searched neurological disease, such as an improvement or a degradation.
  • the evolution of the searched neurological disease is determined with respect to a plurality of first physiological features obtained for the patient 13, represented, for instance, by an average of information representative of first physiological features.
  • the steps 501, 502, 503, 504 of the method described in relation with Figs. 5 and the steps 601, 602, 603, 604, 605, 606, 607, 608, 609 of the method described in relation with Fig. 6 are implemented by the processing module 105 of the acquisition system 10 instead of the processing module 112 of the client device 11.
  • the telemedicine system doesn't require image and audio compression/ decompression capabilities. Indeed, in that case, the acquisition system 10 transmits directly to the client system 1 1, the information representative of the physiological features identified.
  • the steps 501, 502, 503, 504 of the method described in relation with Figs. 5 and the steps 601, 602, 603, 604, 605, 606, 607, 608, 609 of the method described in relation with Fig. 6 are implemented by a processing module of a processing system comprised in the telemedicine system but independent of the acquisition system 10 and the client system 11.
  • the processing system communicates with the acquisition system 10 and the client system 11 via a network.
  • the processing system receives compressed sensor signals comprised in a transport stream from the acquisition system 10 and transmits information representative of the physiological features identified to the client system 11.
  • the processing system could be positioned at a different geographical position than the acquisition system 10 and the client system 11.
  • steps 501 and 502 are implemented by the acquisition system 10 and steps 503 and 504 are implemented by the client system 11 or steps 501 and 502 are implemented by the processing system and steps 503 and 504 are implemented by the client system 11 or step 501 is implemented by the acquisition system 10, step 502 and 503 are implemented by the processing system and step 504 is implemented by the client system 1 1.
  • the systems, modules and means of the telemedicine system located at the same geographical position are comprised in a same integrated apparatus.

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Abstract

L'invention concerne un système de télémédecine permettant d'obtenir un attribut physiologique d'un être vivant à distance, qui comprend : un système d'acquisition comprenant un dispositif multicapteur pourvu d'une pluralité de capteurs, chaque capteur fournissant un signal de capteur comprenant des informations se rapportant à l'être vivant ; un module de traitement pour traiter des signaux de capteur comprenant des moyens d'extraction (501) pour extraire des premières informations représentant un attribut physiologique recherché d'un être vivant à partir d'un premier signal de capteur ; des moyens de recherche (502) pour rechercher des secondes informations représentant l'attribut physiologique recherché dans au moins un second signal de capteur ; et des moyens d'identification pour identifier un attribut physiologique en fonction des premières informations et des secondes informations corrélées avec les premières informations. Le système de télémédecine comprend en outre un système client comprenant un dispositif d'affichage pour afficher (504) des données représentant les attributs physiologiques identifiés reçues en provenance du module de traitement, le système d'acquisition et le système client étant positionnés au niveau de différentes positions géographiques.
PCT/IB2015/000944 2015-03-12 2015-03-12 Système de télémédecine utilisant un dispositif d'acquisition multicapteur Ceased WO2016142734A1 (fr)

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2002082999A1 (fr) * 2001-04-10 2002-10-24 Battelle Memorial Institute Systeme d'analyse d'images et procede de separation des mouvements d'un individu
US20070270665A1 (en) * 2006-05-05 2007-11-22 Chang-Ming Yang Physiological Function Monitoring System
US20130096441A1 (en) * 2010-10-01 2013-04-18 Flint Hills Scientific, Llc Detecting, quantifying, and/or classifying seizures using multimodal data
US20130245502A1 (en) * 2005-11-01 2013-09-19 Earlysense Ltd. Methods and system for monitoring patients for clinical episodes
US20140172310A1 (en) * 2012-12-19 2014-06-19 Elwha Llc Systems and methods for controlling acquisition of sensor information

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2002082999A1 (fr) * 2001-04-10 2002-10-24 Battelle Memorial Institute Systeme d'analyse d'images et procede de separation des mouvements d'un individu
US20130245502A1 (en) * 2005-11-01 2013-09-19 Earlysense Ltd. Methods and system for monitoring patients for clinical episodes
US20070270665A1 (en) * 2006-05-05 2007-11-22 Chang-Ming Yang Physiological Function Monitoring System
US20130096441A1 (en) * 2010-10-01 2013-04-18 Flint Hills Scientific, Llc Detecting, quantifying, and/or classifying seizures using multimodal data
US20140172310A1 (en) * 2012-12-19 2014-06-19 Elwha Llc Systems and methods for controlling acquisition of sensor information

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