Method and computing device for assisting evaluation of head injurity of a subject

Abstract

A method is disclosed for assisting in evaluating a head injury to a subject caused by a fall event occurring on the subject. The method is performed by a processor and includes the steps of: upon detection of a fall event, obtaining measurement data of the fall event over a period of time including the fall event; and generating an indication for aiding in evaluating the head injury based on the measurement data. The indication includes an animated fall trajectory of the subject's head during the fall event and within a space in which the fall occurs, and velocity data of the subject's head during the fall event.

Description

Technical Field

[0001] The present disclosure relates generally to the field of fall detection, and more particularly to a method and computing device for assisting in assessing head injuries to a subject caused by a fall event occurring to the subject. Background Art

[0002] In today's modern world, a major health risk for vulnerable groups, including the elderly, the frail, or the disabled, is injuries caused by accidental falls, such as in the bathroom. A fall, defined as an uncontrolled and sudden displacement of a person's body to the ground or floor, can cause serious health problems or even death if left unnoticed.

[0003] While physical injuries from falls, such as bruises or broken bones, can be noticed by the person or subject who fell or a caregiver, injuries or damage to the brain from falls are sometimes not as easy to detect. Delays in identifying such head injuries can have serious consequences.

[0004] The healthcare industry has developed various technologies to monitor and alert people to falls. Currently, automatic fall detection based on various information-gathering devices (including wearable devices and cameras) is available on the market.

[0005] Some camera-based elder care solutions have gone beyond simply sending notifications after a fall is detected. For example, existing fall detection systems offer advanced injury assessment assistance. If a fall occurs, caregivers can immediately access the fall detection system's video feed to help screen for injuries, assess the severity of the incident, and determine whether a trip to the emergency room is necessary.

[0006] One issue with camera-based fall detection solutions is that users may have privacy concerns, especially in areas such as bathrooms or toilets. Furthermore, injury assessment or assessment assistance based on video playback relies heavily on the subjective judgment of the person viewing the video, and therefore lacks objective information to support a better assessment.

[0007] When it comes to head injuries from falls, they are even more difficult to detect based on images or videos captured by cameras.

[0008] Considering the above, it is expected that fall detection solutions can better assist injury assessment (especially assessment of head injuries) while protecting privacy and considering additional assessment supporting information. Summary of the Invention

[0009] In a first aspect of the present disclosure, a method for assisting in assessing head injury caused to a subject by a fall event is proposed. The method is executed by a processor and comprises the following steps:

[0010] - after detecting a fall event, obtaining measurement data of the fall event over a time period including the fall event;

[0011] - generating indications based on the measurement data to assist in the assessment of head injuries,

[0012] The instructions include:

[0013] Animated fall trajectory of the subject's head during the fall event and in the space where the fall occurred, and

[0014] Velocity data of the subject's head during a fall event.

[0015] The present disclosure is based on the insight that a better aided assessment of a head injury resulting from a fall event occurring to a subject can be provided by relying on an aided assessment indicator of head injury. The indicator comprises an animated fall trajectory of the subject's head during the fall, combined with velocity data of the subject's head. Both the animated fall trajectory and velocity data of the subject's head during the fall are derived from measurement data of the fall event, such as collected by a fall detection system.

[0016] When a fall event is detected, according to the method of the present disclosure, measurement data of the fall event over a time period including the fall event, provided by a fall detection system that detects the fall event, is obtained and used to generate an animated fall trajectory and velocity of the subject's head. The animated fall trajectory is depicted in the space where the fall event occurred. The animated fall trajectory of the subject's head, along with the velocity data of the subject's head, is then used to assist personnel in evaluating or assessing any possible head injury that may have occurred to the subject.

[0017] When the fall trajectory is animated in the space where the fall occurred, the source of the subject's head injury can be identified, such as the head hitting an object in the space.

[0018] The velocity of a subject's head during a fall is an objective parameter (which accounts for factors such as the intensity of the head's collision with an object) and is used as an objective factor or indicator for accurately assessing head injuries.

[0019] This indication of the present invention helps make the assessment of head injuries more accurate because the method utilizes objective indicators derived from measurement data of the fall event. The method also avoids any privacy issues that may arise because no images of the subject are directly used to detect or assess any injuries that occurred to the subject.

[0020] In an example of the present disclosure, measurement data of a fall event is obtained by a ranging sensor by measuring ranging data of different body parts of a subject at multiple moments in a time period including the fall event.

[0021] Rather than taking a photo of the target, the ranging sensor monitors the target within its field of view by measuring the distance between the sensor and each point or part of the target. This measurement data does not include any visual representation of the monitored subject's body. Therefore, there is absolutely no risk of privacy violation.

[0022] In this sense, no image of the subject is even generated. Solutions based on odometry sensors can also extract a matchstick skeleton of the subject from the odometry data, which is also not a direct use of images.

[0023] In an example of the present disclosure, the odometry data at each moment in the time period includes multiple positions of different body parts of the subject, and the subject's animated fall trajectory is generated in the following manner:

[0024] - arranging the positions of the subject's head in order from the earliest moment to the latest moment of the time period including the fall event to obtain a curve representing the movement trajectory of the subject's head during the time period including the fall event;

[0025] - setting the curve relative to a pre-generated three-dimensional plan view comprising the spatial position(s) and dimensions of at least one fixed object in the space where the fall occurred.

[0026] Although the ranging sensor does not capture any direct visual representation of the fallen subject, the ranging sensor can measure the distances to different body parts of the subject, i.e., determine the positions of the different body parts of the subject, e.g., relative to the ranging sensor. A range map that allows identification of the different body parts of the subject can be constructed based on the ranging data.

[0027] Therefore, the measurement data including the positions of different body parts of the subject can be used to obtain a curve representing the motion trajectory of a specific body part (including the head) of the subject. The motion trajectory at each moment of the fall event is animated over time to form an animated fall trajectory of the subject.

[0028] When the subject's animated fall trajectory is compared with a plan view including the spatial position and dimensions of at least one fixed object in the space where the fall occurred, a caregiver or medical staff is allowed to visually see whether the subject's head experienced any movements that could cause head injury.

[0029] In an example of the present disclosure, the step of generating an indication for assisting assessment of head injury based on the measurement data further includes:

[0030] - during a fall event, generating distance data between the subject's head and at least one fixed object in the space where the fall occurred based on the measurement data, based on the position of the subject's head and the spatial position of the at least one fixed object.

[0031] Using the distance of the subject's head at each moment during the fall event available from the measurement data and a plan view including one or more fixed objects in the space where the fall occurred, the distance between the subject's head and each of the at least one fixed object is calculated at each time instance by referring to a pre-generated plan view including the spatial position and size of the at least one fixed object, thereby generating distance data between the subject's head and the at least one fixed object.

[0032] This distance data between the subject's head and one or more fixed objects in the space where the fall occurred is also used to assist in assessing the severity of head injuries caused by the fall. Because the combination of different indicators allows for an objective assessment of the injuries caused by a fall, a much more reliable assessment can be obtained.

[0033] In an example of the present disclosure, a ranging sensor obtains a pre-generated three-dimensional plane map by measuring ranging data of objects in the space where the fall occurs.

[0034] The same ranging sensor used to acquire measurement data for fall events can be used to measure any potential falls in the monitored space to pre-generate a floor plan that includes fixed objects in the space, such as a washbasin or toilet in a bathroom.

[0035] In an example of the present disclosure, the method further includes the step of presenting on a display device an indication for assisting in the assessment of the head injury.

[0036] Those skilled in the art will appreciate that the generated indications for assisting in the assessment of head injuries can be provided to relevant personnel, such as medical personnel or caregivers, allowing them to use the indications in a manner they prefer.

[0037] On the other hand, the method of the present disclosure may also include such an indication for assisting in the assessment of the head injury presented or displayed on a display device that is communicatively coupled or connected to the processor for performing the method of the present disclosure. This is very convenient, especially when the processor and the display device are combined into a single device (which allows for more efficient display of the indication), allowing the assessment of the head injury to be performed immediately after the relevant person becomes aware of the fall event, without any delay.

[0038] In an example of the present disclosure, the method further includes the following steps:

[0039] - finding one or more points on the animated fall trajectory of the subject's head that have a minimum distance to each of at least one fixed object, and

[0040] -When the minimum distance to one of the at least one fixed object is less than a threshold value, highlighting a point on the animated fall trajectory that has the minimum distance to one of the at least one fixed object.

[0041] As will be appreciated by those skilled in the art, the distance between a subject's head and a portion of a fixed object provides, in a sense, an objective criterion for determining whether a subject's head has collided with an object. It is not influenced by subjective impressions and is therefore a clear indicator that the head has been struck by something, a well-founded factor to consider when evaluating any possible head injury.

[0042] It is also possible that the head may hit an object and then bounce and then hit the object again one or more times. Highlighting the point(s) of the animated fall trajectory with the distance between the subject's head and at least one fixed object (which is less than a threshold) helps to draw the attention of relevant personnel to these points and enables them to assess head injuries in a faster and more reliable manner.

[0043] In an example of the present disclosure, the method further includes the following steps:

[0044] -Highlights the velocity of the subject's head in the instance corresponding to the highlighted point on the animated fall trajectory.

[0045] In addition to considering the distance between the subject's head and fixed objects in the space where the fall occurred, the velocity of the head can also be considered. The head velocity of the highlighted point(s) where the distance between the subject's head and the fixed object is highlighted allows for a more accurate assessment of whether the head actually impacted the object.

[0046] In an example of the present disclosure, the method further includes the following steps:

[0047] -The distance between the subject's head and the fixed object is highlighted at instances corresponding to highlighted points on the animated fall trajectory.

[0048] When distance data between the subject's head and the fixed object is also available, the distance between the subject's head and the fixed object is also highlighted for those points highlighted on the animated fall trajectory.

[0049] When the animated fall trajectory, the velocity of the subject's head, and the distance from the subject's head to a fixed object are considered together, the assessment of the severity of the head injury caused by the fall event can be performed with a more accurate degree.

[0050] In an example of the present disclosure, the ranging sensor is a time-of-flight (ToF) sensor.

[0051] ToF sensors, especially low-resolution ToF sensors readily available on the market, are well-suited to performing the measurements required in this disclosure. This helps keep the solution cost-effective.

[0052] A second aspect of the present disclosure provides a computing device comprising a processor, wherein the processor is arranged to execute a method for assisting in assessing a head injury caused to a subject by a fall event according to any aspect of the first aspect of the present disclosure.

[0053] In an example of the present disclosure, a computing device includes a lighting device including an integrated ranging sensor and a processor, wherein:

[0054] The ranging sensor is arranged to obtain measurement data of the fall event over a time period including the fall event.

[0055] An example of a computing device could be a smart light fixture that is currently deployed in many homes. Distance sensors can be easily integrated into light fixtures, saving space and reducing costs.

[0056] In an example of the present disclosure, the ranging sensor is further arranged to obtain measurement data for pre-generating a plan view including the spatial position and size of at least one fixed object in the space where the fall occurs.

[0057] The plan view is generated by a processor based on measurement data obtained by the ranging sensor.Depending on the computing power of the device comprising the processor, the processor may be included in a device separate from the ranging sensor or in the ranging sensor itself.

[0058] In another example of the present disclosure, the ranging sensor is a time-of-flight (ToF) sensor.

[0059] A third aspect of the present disclosure provides a computer program product, comprising a computer-readable storage medium storing instructions, wherein when the instructions are executed on at least one processor, the at least one processor is caused to perform the method according to the first aspect of the present disclosure.

[0060] The above and other features and advantages of the present disclosure will be best understood through the following description with reference to the accompanying drawings. In the accompanying drawings, like reference numerals represent the same components or components that perform the same or comparable functions or operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 A fall detection system according to an embodiment of the present disclosure is schematically illustrated.

[0062] Figure 2 (a)-2(c) illustrate a picture of a bathroom, the ranging data of the bathroom, and a 3D floor plan constructed from the ranging data, respectively.

[0063] Figure 3 An embodiment of a method for assisting in assessing a head injury caused to a subject by a fall event occurring to the subject according to the present disclosure is schematically illustrated in a flowchart-type diagram.

[0064] Figure 4 (a) to 4(e) show several snapshots of the rewind animation in time sequence according to the present disclosure.

[0065] Figure 5 Schematically illustrates exemplary movement speed of the head and head-to-toilet distance during a fall process according to the present disclosure. DETAILED DESCRIPTION

[0066] The embodiments contemplated by the present disclosure will now be described in more detail with reference to the accompanying drawings. The disclosed subject matter should not be construed as being limited to the embodiments described herein. Instead, the illustrated embodiments are provided by way of example to convey the scope of the subject matter to those skilled in the art.

[0067] Throughout the specification, the terms "target," "user," "human," and "subject" may be used interchangeably.

[0068] The following describes a method and a computing device (such as a backend server communicating with a fall detection device or a lighting device with fall detection functionality) for assisting in assessing head injuries caused to a subject by a fall event occurring to the subject.

[0069] The method for assisting in the assessment of head injuries proposed in the present disclosure is implemented using a fall detection system based on a ranging sensor. The ranging sensor can be a time-of-flight sensor, particularly a low-resolution ToF sensor, which can help keep the solution of the present disclosure low-cost.

[0070] Figure 1 A fall detection system 10 according to an embodiment of the present disclosure is schematically illustrated. The fall detection system comprises two main components or components: one or more ranging sensors 11 and a computing or processing device or processor 12.

[0071] The ranging sensor 11 can be a low-resolution, 64-area ToF sensor, for example. The ToF sensor 11 can be deployed on the ceiling of a space to be monitored (such as a bathroom). The ToF sensor 11 is arranged to monitor targets in a space by capturing ranging data of the target in real time without capturing any private information. When the target is a person, such ranging data can indicate the person's position and posture. When the target is a fixed object, the ranging data can indicate the spatial position and size of the object.

[0072] The computing or processing device or processor 12 may be a backend server remotely deployed from the sensor 11. In this case, the processor 12 and each of the sensors 11 communicate 19 with each other via a network such as the Internet 18 in a wired or wireless manner.

[0073] The processor 12 is configured to receive data acquired or captured by one or more sensors 11 and store and optionally present such measurement data. The processor may also be arranged to determine, based on the data obtained from the sensors 11, whether the user is experiencing or has experienced a fall event.

[0074] The processor 12 may also be configured to trigger the alarm device 13 when a fall event is detected, for example by sending 17 a trigger message to the alarm device 13 .

[0075] The processor 12 is described above as a separate or independent device from the sensor 11. However, as will be appreciated by those skilled in the art, the processor 12 and the sensor may be a single integrated device.

[0076] As an example, the sensor 11 may include a sensing component and also have a built-in processor that may process the raw data captured by the sensing component of the sensor to determine any possible events occurring to the user.

[0077] It is also possible that the sensor has a built-in processor or a separate local processor for fall detection, with another processor at a back-end or remote location used to generate indications to assist in injury assessment.

[0078] The processor 12 is described above as being remotely disposed from the sensor 11. In practice, the processor 12 may also be locally disposed and communicatively connected to the sensor 11.

[0079] A specific example of a fall detection system contemplated by this disclosure may be a lighting device that integrates a ranging sensor, such as a Time of Flight (ToF) sensor, and a processor. In addition to its inherent lighting function, such a lighting device can also function as a fall detection device or system. When the lighting device has sufficient computing resources available, it can execute the method of this disclosure, described in detail below.

[0080] As an example, the ToF sensor can be based on indoor lighting equipment that is readily available in every home, such as LED lights fixed to the ceiling.

[0081] When the space where the ToF sensor 11 is deployed is vacant, the sensor 11 is arranged to acquire measurement data of the space and send the measurements to the processor 12 to construct a three-dimensional (3D) floor plan of the space. Such a 3D floor plan contains the sizes and positions of fixed objects in the space. As an example, if the space is a bathroom, fixed objects such as a toilet and a washbasin can be illustrated in the 3D floor plan.

[0082] Figure 2 (a) to (c) illustrate a picture of a bathroom, distance measurement data of the bathroom, and a 3D floor plan of the bathroom constructed based on the distance measurement data, respectively. The distance measurement data is obtained using, for example, a 64 (8x8) area ToF distance measurement sensor.

[0083] refer to Figure 2 (b) This ToF sensor can simultaneously output 64 range measurements (regions 1 to 64) within a single frame, representing the distance from any object within its detection range to the sensor. The measurement frequency of a ToF sensor can range from a few frames per second (FPS) to tens of FPS.

[0084] Specifically, Figure 2 (a) is a photograph 21 of a portion of a vacant bathroom including a washbasin 22 and a toilet 23.

[0085] Figure 2 (b) is a frame output of a 64-area ToF sensor mounted on the bathroom ceiling 24. The sensor’s field of view (FoV) covers the toilet 23 and part of the washbasin 22.

[0086] Figure 2 (c) is obtained by a computing device (such as a backend computing device) using a ToF sensor Figure 2 (b) The 3D plan view 25 generated from the data of FIG. The size and position of the fixed objects in the bathroom (ie, the toilet 23 and the wash basin 22) are known from the 3D plan view 25. In practice, it is not necessary to know exactly what the fixed objects are.

[0087] Figure 2 Both (b) and 2(c) show a wash basin 22 and a toilet 23.

[0088] Figure 3 An embodiment of a method 30 for assisting in assessing a head injury caused to a subject by a fall event occurring to the subject according to the present disclosure is schematically illustrated in a flowchart-type diagram.

[0089] The 3D plan view of the space where the fall event occurred is pre-generated by a computing device that executes the method for assisting in the assessment of head injuries. Alternatively, such a 3D plan view can be obtained from another device that has pre-generated a 3D plan view.

[0090] At step 31, when a fall detection system detects a fall event, a computing device or processor executing the method of the present disclosure obtains measurement data of the fall event that occurred to a subject or user of the fall detection system. The measurement data continues for a period of time including the fall event.

[0091] In practice, when a person is present in a space where a ToF sensor has been deployed, the ToF sensor starts monitoring the person's movements and postures. The sensor continuously records measurement data for a predefined duration (such as a period of the past 20 seconds).

[0092] Alternatively, to reduce the size of recorded data, the sensor can record measurements only for the areas covering a person. The number of areas covering a person is not constant. When a person is standing or sitting, they may occupy up to eight areas. When a person is fallen or lying on the floor, they may occupy up to 12 areas.

[0093] If a person falls, a fall detection system including a ToF sensor can detect the fall shortly after the person's body comes to rest on the floor. Detection of a fall is beyond the scope of this disclosure and will not be described further herein.

[0094] At the moment a fall is detected, the recorded data will contain measurement data covering the complete fall process that the person experienced. The ToF sensor can now stop recording the measurement data and send the recorded measurement data (optionally together with the fall alert) to a computing device, such as a backend server, that performs a method to assist in the assessment of head injuries.

[0095] As described above, for each moment in time, the measurement data includes ranging data or distances (from the ToF sensor) of different body parts of the subject.

[0096] At step 32 , an indication is generated based on the measurement data to assist in the assessment of the head injury.

[0097] Instructions for assisting in the assessment of head injuries may be generated and provided to the user, allowing the user to display the instructions in an appropriate manner. Alternatively, when a computing device including a processor for executing the method of the present disclosure is equipped with or communicatively connected to a display device, the instructions may be presented or displayed directly on the display device at step 33.

[0098] As an example, during a fall, an animated fall trajectory of the subject's head, as well as the subject's head velocity and, optionally, the distance between the subject's head and one or more fixed objects during the fall (all of which will be described below), can be presented on a display device, allowing medical personnel or caregivers to assess the severity of the head injury in an objective and reliable manner.

[0099] The indication may include an animated fall trajectory of the subject's head during the fall event and within the space where the fall occurred, as well as head velocity data of the subject during the fall event.

[0100] The animated fall trajectory of the subject's head and the subject's head velocity can be generated in any order. There is no need to generate a specific one before the other.

[0101] For injury assessment, it is important to know whether a person who has fallen struck their head on a fixed object, such as a toilet or washbasin, during the fall and, if so, how severe the blow to the head was.

[0102] The animated fall trajectory generated by the present disclosure and the subject's head velocity can be used to determine whether such an impact occurred, thereby assisting in assessing the subject's head injury.

[0103] In an example, a backend server serving as a computing device for executing the method of the present disclosure analyzes recorded measurement data to generate a playback animation of the falling process.

[0104] As one skilled in the art will appreciate, for each moment of the fall process, the ToF sensor records multiple distances to different parts of the subject's body. When arranged sequentially from the earliest moment to the latest moment in the time period including the fall event, the distances to the subject's head will form a curve that represents the movement trajectory of the subject's head during the time period including the fall event. When the curves obtained at different moments of the fall process are played back in an animated manner, the fall process is visualized against a 3D plan view of the space where the fall occurred.

[0105] In the playback animation, the movement trajectory of the person's head can be highlighted compared to the changes in the person's posture during the fall process. Figure 4 (a) to 4(e) show several snapshots of the fall playback animation in chronological order.

[0106] refer to Figure 4 (a), a straight line segment 41 represents a standing person, and a small dot 42 on the top of the straight line segment 41 represents the person's head. Figure 4 The curve 43 formed by the small triangles 42 shown in each of (b) to 4(e) illustrates the trajectory of the person's head throughout the fall.

[0107] The curve 43 is plotted relative to a 3D plane diagram representing the space in which the fall event occurred, allowing the possible sources of head injuries, such as the head hitting an object, to be identified in a straightforward manner.

[0108] Figure 4 (b) indicates that the fall has just begun, as the curve 43 shows that the head has just started to move downward. Figure 4 As can be seen from the curve 43 in (c), the head is moving toward the toilet 23 and is about to hit the toilet 23. Figure 4 (d) shows the moment when the head contacts the toilet bowl 23. Figure 4 (e) The fall ends when the person lies on the floor.

[0109] To further confirm whether the person's head hit the toilet and the severity of the impact, the backend calculates the person's head movement speed, which is used as a further indicator to assist in assessing head injuries. Based on the animated fall trajectory and the movement speed of the person's head, a better assessment result can be obtained.

[0110] By using the measurement data, the distance between the person's head and a fixed object in the space where the fall occurred (such as the top surface of a toilet) can also be obtained. This is used as a further indicator to assist in the assessment of head injuries.

[0111] Those skilled in the art will understand that the moving speed of the subject's head is calculated by dividing the distance difference between the head and an object such as a toilet at this moment and the previous moment by the time difference between this moment and the previous moment.

[0112] As for the distance data to the object, it is determined using the distance data of the subject's head measured and the distance data of the object measured in advance when generating the 3D plan view of the space where the fall occurred.

[0113] Figure 5 Schematic illustration of exemplary movement speed of the head and head-to-toilet distance during a fall process.

[0114] exist Figure 5 In the example, the horizontal axis is the frame index relative to time. For example, when the FPS is 10, one frame is 0.1 seconds. Figure 5 The lower part is the vertical speed of the head in meters per second (m / s); and Figure 5 The upper part is the distance from the head to the top surface of the toilet, in centimeters (cm).

[0115] Figure 5 The entire fall process is covered, and there are 6 dashed lines indicating several moments during the fall. Figure 5 The first straight line A in Figure 4 (b) is the same as the moment when the fall begins. Figure 5 This is reflected in the head speed starting to increase and the distance between the head and the toilet 23 starting to decrease.

[0116] Figure 5 The second straight line B and Figure 4 (c) shows the moment when the head of the person is about to hit the toilet. At this moment, the speed of the head reaches its maximum (~0.8 m / s), and after this moment, the speed of the head drops sharply, from about 0.8 m / s to 0.3 m / s in 0.1 seconds, which confirms that the head hit the toilet.

[0117] The velocity of the head before impacting the toilet and the change in velocity during impact are important information for assessing the severity of the impact.

[0118] Figure 5 The third straight line C and Figure 4 (d) is the same as the moment when the person's head is in contact with the toilet. After this moment, the speed of the head increases for a short period of time, reflecting that the head bounces off the toilet surface.

[0119] Then, the speed and distance continue to decrease until Figure 5 The fourth straight line D shows the moment when the person's head and his / her upper body are stationary on the toilet until Figure 5 The fifth straight line E shows the moment.

[0120] From the moment E, the upper body of the person begins to fall toward the floor and lies completely on the floor at the moment of the sixth straight line F, which is consistent with the Figure 4 During this period, the velocity of the head increases again and then decreases, while the distance of the head decreases further below zero, indicating that the head is below the top surface of the toilet.

[0121] Head injuries are more likely to be caused by the head striking an object. In the present disclosure, the head striking an object can be indicated by several parameters or indicators obtained from the measurement data. Such parameters or indicators include the distance between the head and the object, the speed of the head when it strikes the object, and the change in speed before and after the head strikes the object.

[0122] Another factor to consider is that when the head strikes an object and then bounces off and strikes the object a second or even a third time, this is a combination of forces such as gravity and the force of impact between the head and the object.

[0123] When assessing a head injury inflicted on a subject based on an animated fall trajectory, the velocity of the subject's head and the distance between the subject's head and one or more fixed objects, the moment of minimum distance between the subject's head and one or more fixed objects, and / or significant changes in the velocity of the subject's head are considered relative to each other. This allows for a more accurate assessment of possible head injuries.

[0124] Information of particular interest to the medical professional or caregiver may be highlighted to draw the attention of the medical professional or caregiver viewing the displayed indications to assist in the assessment of the head injury.

[0125] Thus, at step 34, one or more of the presented indications are highlighted.

[0126] As an example, one or more points on the animated fall trajectory of the subject's head that have a minimum distance to each of at least one fixed object can be determined. When the minimum distance to one of the at least one fixed object is less than a threshold, such as 20 cm, the point of the animated fall trajectory having such a distance is highlighted.

[0127] In addition, if Figure 5 The gray area indicated by the figure can also highlight the subject's head and the distance between the subject and the fixed object at a certain moment or a time period including a certain moment when the subject hits his or her head against the object. This further helps medical personnel or caregivers make a quick and accurate assessment of the subject's head injury.

[0128] Those skilled in the art will appreciate that the assessment results can be presented to medical staff or caregivers together with the animated fall trajectory, the speed of the subject's head, and the distance between the subject's head and one or more fixed objects, allowing them to evaluate the entire situation based on professional experience.

[0129] The present disclosure is not limited to the examples disclosed above and may be modified and enhanced by those skilled in the art outside the scope of the present disclosure disclosed in the appended claims without applying creative skills and for use in any data communication, data exchange and data processing environment, system or network.

Claims

1. A method (30) for assisting in assessing a head injury caused to a subject by a fall event occurring to the subject, the method (30) being executed by a processor and comprising the following steps: - after detecting the fall event, obtaining (31) measurement data of the fall event over a time period including the fall event; - generating (32) an indication for assisting in the assessment of head injuries based on the measurement data, The instructions include: Animated fall trajectory of the subject's head during the fall event and in the space where the fall occurred, and Velocity data of the subject's head during the fall event, The step of generating an indication for assisting in the assessment of head injury based on the measurement data further comprises: - during a fall event, generating distance data between the subject's head and at least one fixed object in the space where the fall occurred based on the measurement data, based on the position of the subject's head and the spatial position of the at least one fixed object.

2. The method (30) according to claim 1, wherein the measurement data of the fall event is obtained by a ranging sensor by measuring the ranging data of different body parts of the subject at multiple moments in a time period including the fall event.

3. The method (30) according to claim 2, wherein the odometry data at each moment in the time period includes a plurality of positions of different body parts of the subject, and the animated fall trajectory of the subject is generated by: - arranging the positions of the subject's head in order from the earliest moment to the latest moment of the time period including the fall event to obtain a curve representing the movement trajectory of the subject's head during the time period including the fall event; - setting the curve relative to a pre-generated three-dimensional plan view comprising the spatial position(s) and dimensions of at least one fixed object in the space where the fall occurred.

4. The method (30) according to claim 3, wherein the ranging sensor obtains the pre-generated three-dimensional plane map by measuring ranging data of objects in the space where the fall occurs.

5. The method (30) according to any one of the preceding claims, further comprising the step of presenting on a display device an indication for assisting in the assessment of the head injury.

6. The method (30) according to claim 5, further comprising the steps of: - finding one or more points on the animated fall trajectory of the subject's head that have a minimum distance to each of at least one fixed object, and - When the minimum distance to one of the at least one fixed object is less than a threshold value, highlighting (34) a point on the animated fall trajectory that has the minimum distance to one of the at least one fixed object.

7. The method (30) according to claim 6, further comprising the steps of: - Highlight (34) the velocity of the subject's head in the instance corresponding to the highlighted point on the animated fall trajectory.

8. The method according to claim 6 or 7, further comprising the steps of: - Highlight (34) the distance between the subject's head and the fixed object at instances corresponding to highlighted points on the animated fall trajectory.

9. The method according to any of the preceding claims, wherein the ranging sensor is a time-of-flight (ToF) sensor.

10. A computing device comprising a processor arranged to execute the method according to any one of the preceding claims 1 to 9 for assisting in the assessment of head injury to a subject caused by a fall event occurring to the subject.

11. The computing device of claim 10, comprising a lighting device including an integrated ranging sensor and processor, wherein: The ranging sensor is arranged to obtain measurement data of the fall event over a time period including the fall event.

12. The computing device according to claim 11, wherein the ranging sensor is further arranged to obtain measurement data for pre-generating a plan view including a spatial position and size of at least one fixed object in the space where the fall occurred.

13. The computing device of claim 11 or 12, wherein the ranging sensor is a time-of-flight (ToF) sensor.

14. A computer program product comprising a computer-readable storage medium storing instructions which, when executed on at least one processor, cause the at least one processor to perform the method according to any one of the preceding claims 1 to 9.

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