A monitoring system for monitoring the usage status of medical devices, a medical device, and a monitoring method.

Abstract

To make it possible to identify causes that may lead to damage to a medical device by monitoring corresponding usage conditions, and to record appropriate data for predictive diagnosis.SOLUTION: A monitoring system (20) comprises: an accelerometer (22) adapted to detect acceleration of a medical device (10) during handling of the medical device (10); a sensor unit (24) adapted to detect a further condition of the medical device (10) during handling of the medical device (10); and a control unit (26) with a dedicated storage unit (26a), wherein the control unit (26) is operatively connected to the accelerometer (22) and the sensor unit (24) and adapted to derive use data of the medical device (10) from the output data of the accelerometer (22) and the sensor unit (24) and to differentiate based on the respective output data of the accelerometer (22) and the sensor unit (24) between a regular use state and an unintended use state of the medical device (10).SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a monitoring system for monitoring the usage status of a medical device, a medical device including such a monitoring system, and a monitoring method for operating such a medical device.

Background Art

[0002] In order to ensure the proper operation of medical equipment and devices, it is necessary to regularly inspect the aforementioned devices because their malfunctions may cause serious failures during critical therapeutic or surgical interventions on patients. However, currently, the inspection of medical equipment and devices is mainly carried out by visual inspection to identify external damage or disassembly to identify internal damage after internal damage is recognized because the device does not function as expected during use.

[0003] Therefore, predictive techniques that enable the identification of damage expected or already occurring in medical devices before they are used are not used so that malfunctions or unexpected behaviors during medical treatment can be avoided in advance. Furthermore, only the possibility of damage to medical devices can be identified by disassembling the corresponding devices, and high costs and long downtimes of the devices are expected, resulting in higher operating costs and general inconveniences for the users of the aforementioned devices.

[0004] In particular, the trauma of medical devices such as endoscopes or hand-held instruments can be identified by visual inspection by trained experts, but internal defects caused by physical stress can only be identified after disassembly or through side effects such as image loss or other functions not functioning properly as expected.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

[0006] Therefore, an objective of the present invention is to enable the identification of potential causes of damage to medical devices by monitoring corresponding usage conditions and to record appropriate data for predictive diagnosis. [Means for solving the problem]

[0007] For this purpose, the present invention proposes a monitoring system for monitoring the usage status of a medical device, comprising: an accelerometer adapted to detect the acceleration of the medical device during handling of the medical device; a sensor unit adapted to detect further conditions of the medical device during handling of the medical device; and a control unit having a dedicated memory unit, wherein the control unit is operably connected to the accelerometer and the sensor unit, derives usage data of the medical device from the output data of the accelerometer and the sensor unit, and is adapted to distinguish between normal and unintended usage conditions of the medical device based on the respective output data of the accelerometer and the sensor unit.

[0008] Accordingly, the present invention provides a monitoring system in which two different sensor units are used to monitor the usage of a medical device of interest, and a control unit based on the provided data can distinguish whether the corresponding medical device is being used in the intended manner or whether an event has occurred that would cause the medical device to be in a state where damage should be expected or at least suspected. In particular, by using an accelerometer as the primary sensor unit, it is possible to detect and record typical usage patterns expected during proper handling or operation of the device, for example, while performing medical procedures or other expected situations such as storing, sterilizing, and transporting the aforementioned device, while also detecting unexpected events with excessive acceleration values, such as impacts or drops with potentially harmful collision parameters. By adding sensor units, classification, refinement, verification, and inspection of the data provided by the accelerometer can be performed, and the data provided by the accelerometer and sensor units can be processed by the control unit in an advantageous manner, as further described below.

[0009] In one possible embodiment, the sensor unit may also be formed by a second accelerometer, which may be of a different type from the first accelerometer, and preferably have a larger measuring range, particularly up to at least 200g. Although such accelerometers with extended measuring ranges have become available in recent years, their power consumption is still significantly higher compared to conventional accelerometers that are optimized for low, insufficient power consumption within their reduced measuring range.

[0010] In alternative embodiments, different types of sensors can be used as further sensor units. Possible types of sensors include microphones for detecting sound waves, piezoelectric elements for detecting pressure, and temperature sensors. All of the aforementioned types of sensors can directly or indirectly detect collisions with or against the medical device in question, which may be classified as unintended use conditions in the sense of the present invention.

[0011] To further optimize the power consumption of the corresponding monitoring system according to the present invention, the sensor unit, in particular the second accelerometer, may be configured to normally be in a low-power standby mode and to transition to a functional mode only when a threshold is detected. The aforementioned threshold may relate to a value of further conditions or threshold acceleration that the sensor unit itself is monitoring. Thus, in embodiments using the second accelerometer, the second accelerometer can switch from its low-power standby mode to its functional mode only when a certain acceleration is exceeded, and the corresponding signal may be provided by the second accelerometer itself, if it can itself transition from its low-power standby mode to its functional mode. In such embodiments, during standby mode, acceleration data is recorded less frequently, or only in relation to whether the aforementioned threshold has been reached, and as soon as the threshold is reached, very fine and accurate acceleration data is acquired and recorded in functional mode. On the other hand, in other embodiments, the second accelerometer can also transition to its functional mode as soon as it detects that a threshold acceleration value has been reached, for example, when it receives an activation signal from the first accelerometer or control unit from an external source. Similarly, the first accelerometer may also be provided with a low-power mode and, upon detecting a small amount of movement, transition to its fully functional mode to provide appropriate data to the control unit.

[0012] The second accelerometer may have a measuring range of up to 200g, while the first accelerometer, in contrast, has a measuring range of at least 16g, preferably at least 32g. Such accelerometers are widely available on the market and are low power consumption, so they are used, for example, in mobile phones and smartwatches to track the normal movement of the wearer or user, respectively.

[0013] Different methods may be used to distinguish between normal and unintended usage conditions, but in certain embodiments, the control unit may be adapted to distinguish between the two usage conditions based on machine learning data previously recorded in the control unit's memory unit. For example, before shipping the monitoring system according to the present invention, extensive experiments can be conducted with a corresponding medical device that includes the monitoring system and is exposed to both normal and unintended usage conditions, and the collected data can be used as training data for an artificial intelligence machine learning system, such as a neural network.

[0014] The monitoring system according to the present invention may further comprise a communication unit, particularly a wireless communication unit, operably coupled to the control unit. By providing the aforementioned communication unit, data recorded by the accelerometer and sensor units, as well as data processed by the control unit, can be transmitted in real time, intermittently, or upon user request to an external data processing system, enabling external diagnostics regarding the past use of the corresponding medical device.

[0015] Additionally or alternatively, the control unit may be further adapted to record usage data in a storage unit for later retrieval, for example, during routine inspections of the corresponding medical device, so that the recorded usage data can be read out to investigate the past usage of the medical device and perform a diagnosis.

[0016] The control unit may also be adapted to use artificial intelligence to distinguish between normal and unintended use of the medical device, for example, a neural network in which corresponding data provided by accelerometers and sensor units serves as input.

[0017] In a further aspect, the present invention relates to a medical device, particularly a reprocessable medical device, equipped with the monitoring system according to the present invention described above. In this regard, a reprocessable medical device is understood to be a multi-purpose medical device that can be processed in an autoclave, for example, for sterilization between uses. On the other hand, the monitoring system according to the present invention can, of course, also be used in disposable devices, for example, to ensure proper handling before medical use, during manufacturing and / or transport.

[0018] The corresponding medical device may further be equipped with a standalone power supply, particularly a rechargeable power supply, so that its use and handling can be monitored even when an external power supply is not readily connected. For example, in the case of an endoscope, during surgical procedures, the endoscope is connected to an external power supply that can also be used to power the sensor unit and the control unit of the monitoring system described above, but by providing the medical device with an additional standalone power supply, proper handling of the device can also be monitored during times when the device is being transported, sterilized, or otherwise handled without access to the external power supply.

[0019] As briefly stated above, the present invention can be incorporated into any conceivable type of medical device, but it may particularly relate to endoscopes or cases for endoscopes. Therefore, it should be understood that medical devices in the sense of the present invention relate not only to surgical instruments or similar devices that come into direct contact with the patient, but also to auxiliary equipment used to handle and transport such medical devices, such as the aforementioned cases or different types of auxiliary devices. By monitoring the usage status of such auxiliary equipment, it is possible to easily detect any damage that may occur to the devices being transported therein or used in combination therewith.

[0020] In yet another aspect, the present invention relates to a monitoring method for operating the monitoring system or medical device described above, comprising: continuously monitoring the acceleration of the medical device with an accelerometer; monitoring further conditions of the medical device at least temporarily with a further sensor unit; and using a control unit to derive usage data of the medical device from the output data of the accelerometer and the sensor unit, and distinguishing between normal and unintended usage conditions of the medical device based on the respective output data of the accelerometer and the sensor unit.

[0021] The monitoring method may further include performing machine learning initially and / or repeatedly on the medical device or different medical devices of the same type to achieve both normal and unintended usage conditions before using the aforementioned medical device in its intended monitoring method and circumstances.

[0022] One example of a machine learning technique that can be used in this context is to detect the connection status of a medical device to an external device, such as a video processor, and to evaluate the movement pattern of the medical device based on the detected connection status. This approach generally relies on using different thresholds for different use cases of the device, and in a specific example of its disconnection from a video processor, the device may move, for example, from an operating room to a cleaning department, during which a different movement pattern is expected compared to the use of the device during a medical procedure. By calculating the corresponding duration and measuring the movement pattern, it is possible to further distinguish the next step, such as manual cleaning. By using artificial intelligence, the understanding of this usage stage of the device can be improved / learned over time. This makes it possible to distinguish the typical duration for each identified usage stage, and based on this, threshold settings can be adjusted to improve system sensitivity, or vice versa. Such processing and learning for each typical usage stage of the corresponding device can contribute to energy saving by preventing unnecessary device startups and potentially extend battery life.

[0023] Finally, differentiating between the normal and unintended usage states of the device can include classifying collisions of the medical device. For this purpose, the corresponding medical device may be dropped from a predetermined height or may be subjected to collisions in another way that can be classified as acceptable or unacceptable depending on the structural integrity of the device and its general resilience. Based on the recorded experimental data, acceptable collisions can be classified as normal usage states, while overly strong collisions, such as dropping from an overly high height, can be classified as unintended usage states for further use during the operation of the system / device.

[0024] Further features and advantages of the present invention will become more apparent from the following description of its embodiments when viewed in conjunction with the accompanying drawings. These drawings particularly show the following.

Brief Description of the Drawings

[0025] [Figure 1] It is a schematic diagram of a medical device according to the present invention. [Figure 2] It is a schematic diagram of a method for classifying collisions executed by the device of FIG. 1. [Figure 3] It is a flowchart of a method for using the device of FIG. 1 according to the present invention.

Modes for Carrying Out the Invention

[0026] In FIG. 1, a medical device in the form of an endoscope is schematically shown and is generally indicated by reference numeral 10. The endoscope includes a housing 12 and typical functional components such as an image sensor, an optical lens, and a light guide cable that receives light from an external light source, which are known to those skilled in the art and are not shown in FIG. 1 and will not be described in detail below.

[0027] The housing 12 of the endoscope 10 houses a monitoring system 20 according to the present invention, as well as a standalone power supply 14, such as a rechargeable energy storage element in the form of a rechargeable battery and / or an electromechanical energy harvesting unit. The monitoring system 20 comprises a sensor unit formed by an accelerometer 22 for detecting the acceleration of the endoscope 10 during handling of the endoscope 10, and a second accelerometer 24 having a larger measuring range compared to the first accelerometer 22, and a control unit 26 having a dedicated storage unit 26a, the control unit 26 being operably coupled to the two accelerometers 22, 24 and adapted to process the corresponding sensor data provided by the accelerometers 22 and 24.

[0028] Referring now to Figure 2, the process for classifying collisions with the endoscope in Figure 1 is schematically shown. There, the endoscope 10 is dropped from different predetermined heights at predetermined angles or orientations, and corresponding sensor data provided by accelerometers 22 and 24 during the fall and collision are recorded for further analysis.

[0029] The experiment is performed multiple times, and the profiles detected as a result of acceleration representing endoscope collisions are fed into appropriate machine learning-based algorithms to define acceptable and unacceptable collisions to the endoscope. Based on this machine learning, the control unit 26 of the endoscope 10 is provided with appropriate data and algorithms to monitor the endoscope 10 during use and to address whether unexpected strong collisions are occurring. The corresponding data derived by the control unit 26 based on the data provided by the accelerometers 22, 24 can be stored in the storage unit 26a for subsequent reading and / or can be transferred periodically, in real time, or on user request to an external server by wired or wireless communication means 28 also provided in the system 20 within the endoscope housing 12.

[0030] Here, Figure 3 shows a flowchart of the monitoring method according to the present invention for operating a medical device in the form of the endoscope 10 of Figure 1. First, in step S1, before shipping and operating the endoscope 10, machine learning is performed based on exposing the endoscope 10 to both normal and unintended use conditions, and of course, different endoscopes of the same or similar type may be used in the machine learning experiment. Step S1 can be performed, for example, by the method shown in Figure 2 and described above.

[0031] At a specific point in the lifespan of the endoscope 10, for example, when the endoscope 10 has left the factory and been shipped to a customer, the accelerometer 22 begins monitoring the acceleration of the medical device in step S2, and this monitoring is performed continuously to detect any mishandling of the device 10 in different scenarios.

[0032] At least temporarily, if further circumstances of the medical device, and in embodiments expressly described herein, are detected to exceed a threshold acceleration value that activates a second accelerometer to extend the measurement range for acceleration of the device 10, a larger measurement range for acceleration is monitored by the second accelerometer.

[0033] Based on the data provided by the two sensor units 22 and 24 in step S3, in step S4, the control unit 26 distinguishes between normal and unintended use conditions of the medical device 10 and transmits and / or stores the corresponding data for further use. Based on the collected and characterized data, predictive maintenance of the device can be performed, and warnings or alarms can be output at any appropriate time when mishandling of the device is detected as an unintended use condition. [Explanation of Symbols]

[0034] 10. Endoscope (medical device) 12 Endoscope Housing 14 Standalone power supplies 20 Systems 22 First accelerometer 24. Second accelerometer (sensor unit) 26 Control Unit 26a Memory Unit 28 Wired or wireless means

Claims

1. A monitoring system for monitoring the usage status of medical devices, An accelerometer adapted to detect the acceleration of the medical device during handling of the medical device, A sensor unit adapted to detect further states of the medical device during handling of the medical device, A control unit having a dedicated memory unit, Equipped with, A monitoring system comprising: a control unit operably connected to the accelerometer and the sensor unit; a control unit deriving usage data of the medical device from the output data of the accelerometer and the sensor unit; a machine learning-based algorithm distinguishing between normal and unintended usage of the medical device based on the respective output data of the accelerometer and the sensor unit; detecting the connection status of the medical device to an external device which is a video processor; and evaluating the movement pattern of the medical device based on the detected connection status.

2. The monitoring system according to claim 1, wherein the sensor unit is formed by a second accelerometer, the second accelerometer being of a different type from the first accelerometer and having a measurement range of at least 200 g.

3. The monitoring system according to claim 2, wherein the second accelerometer is normally in a low-power standby mode and is adapted to transition to a functional mode when a threshold is detected.

4. The monitoring system according to claim 1, wherein the accelerometer has a measurement range of at least 32 g.

5. The monitoring system according to claim 1, wherein the machine learning-based algorithm is an algorithm that performs machine learning to distinguish between the normal usage state and the unintended usage state based on machine learning data previously recorded in the memory unit.

6. The monitoring system according to claim 1, further comprising a communication unit operably coupled to the control unit.

7. The monitoring system according to claim 1, wherein the control unit is further adapted to record usage data in the storage unit for later reading.

8. A reprocessable medical device comprising the monitoring system described in claim 1.

9. The medical device according to claim 8, further comprising a rechargeable power supply which is a standalone power supply.

10. The medical device according to claim 8, wherein the medical device is an endoscope or an endoscope case.

11. A monitoring method for operating the monitoring system described in claim 1 or the medical device described in claim 8, The acceleration of the medical device is continuously monitored by the accelerometer, The sensor unit monitors the further state of the medical device at least temporarily, A monitoring method comprising: using the control unit to derive usage data of the medical device from the output data of the accelerometer and the sensor unit; using a machine learning-based algorithm to distinguish between normal and unintended usage states of the medical device based on the respective output data of the accelerometer and the sensor unit; detecting the connection status of the medical device to an external device which is a video processor; and evaluating the movement pattern of the medical device based on the detected connection status.

12. The monitoring method according to claim 11, wherein the machine learning-based algorithm is an algorithm which has initially and / or repeatedly performed machine learning on the basis of achieving both normal use and unintended use in the medical device or different medical devices of the same type.

13. The monitoring method according to claim 12, wherein distinguishing between the normal usage state and the unintended usage state includes classifying collisions of the medical device.

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