Method and computing device for assisting in the assessment of a subject's head injury caused by a fall event

Abstract

A method for assisting in the assessment of a subject's head injury caused by a fall event occurring to the subject is disclosed. The method is executed by a processor and includes, upon detection of the fall event, obtaining measurement data of the fall event over a period of time including the fall event, and generating an indication to assist in the assessment of 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 the 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 methods and computing devices for assisting in the assessment of a subject's head injury caused by a fall event occurring to the subject. [Background technology]

[0002] A major health risk in modern society for vulnerable populations, such as the elderly, infirm, or disabled, is injury from accidental falls, such as in the bathroom. Falls, which may be defined as the sudden, uncontrolled movement 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 resulting from a fall, such as bruises or fractures, may be noticeable by the person or object that fell or by a caregiver, brain injuries or damage caused by a fall may not be as easy to detect. Delay in identifying such head injuries can have serious consequences.

[0004] Various technologies have been developed by the healthcare industry to monitor and alarm on fall events occurring in different groups of people. Automatic fall detection based on various information-gathering devices, including wearable devices, cameras, etc., is currently available on the market.

[0005] Some camera-based elder care solutions go beyond simply sending notifications after a fall is detected. For example, some available fall detection systems offer advanced injury assessment assistance. In the event of a fall, care staff can instantly access the fall detection system's fall video to screen for injuries, assess the severity of the incident, and determine whether transport to the emergency room is necessary.

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

[0007] Head injuries caused by falls are even more difficult to detect based on camera-captured images or video. Summary of the Invention [Problem to be solved by the invention]

[0008] In view of the above, it is desirable for a fall detection solution to be privacy-preserving and be able to consider additional assessment support information to better assist injury assessment, particularly injury assessment of head injuries. [Means for solving the problem]

[0009] In a first aspect of the present disclosure, there is provided a method for assisting in the assessment of a head injury in a subject caused by a fall event occurring to the subject, the method being executed by a processor and comprising: - upon detection of a fall event, obtaining measurement data of the fall event over a period of time that includes the fall event; - generating an indication based on the measurement data to assist in the assessment of a head injury; Including, The indication is An animated fall trajectory of the subject's head during the fall event and in the space in which the fall occurs; and Velocity data of the subject's head during the fall event; A method is presented, including:

[0010] The present disclosure is based on the insight that better assistance in assessing a head injury caused by a fall event occurring to a subject can be provided by relying on an indication to assist in the assessment of the head injury. The indication includes an animated fall trajectory of the subject's head combined with velocity data of the subject's head during the fall. Both the animated fall trajectory and the velocity data of the subject's head during the fall are derived from measurement data of the fall event collected, for example, by a fall detection system.

[0011] According to the disclosed method, when a fall event is detected, measurement data of the fall event over a period of time 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 plotted in space in which the fall event occurs. The animated fall trajectory of the subject's head, along with the subject's head velocity data, is used to assist personnel in evaluating or assessing a possible head injury sustained by the subject.

[0012] An animated fall trajectory set in the space where the fall occurs can identify the cause of the subject's head injury, such as the head hitting an object in the space.

[0013] The velocity of a subject's head during a fall, which is an objective parameter that indicates factors such as the force with which the head impacts an object, is used as an objective factor or indicator to accurately assess head injury.

[0014] Such indications of the present invention help to make head injury assessment more accurate because the method utilizes objective metrics derived from measurement data of the fall event. The method also prevents potential privacy issues because images of the subject are not directly used to detect or assess injuries sustained by the subject.

[0015] In one example of the present disclosure, measurement data of a fall event is obtained by measuring ranging data of different body parts of a subject over a number of instants during a period that includes the fall event using a ranging sensor.

[0016] Instead of taking a photograph of the target, the ranging sensor monitors the target within its field of view by measuring the distance between the ranging sensor and each point or part of the target. Such measurement data does not contain a visual representation of the monitored subject's body, and therefore does not pose any risk of violating privacy.

[0017] In this sense, no image of the subject is even generated, and although solutions based on ranging sensors may conceptualize a matchstick-type skeleton of the subject from ranging data, this also does not directly use images.

[0018] In one example of the present disclosure, the ranging data at each moment in time includes multiple positions of different body parts of the subject, and the animated fall trajectory of the subject is calculated by: - sequentially arranging the positions of the subject's head from the earliest moment to the latest moment during the period including the fall event to obtain a curve representing the movement trajectory of the subject's head during the period including the fall event; - setting the curve against a pre-generated three-dimensional floor map including the spatial location and dimensions of at least one fixed object in the space where the fall occurs; It is generated by

[0019] Although the ranging sensor does not capture a direct visual representation of the falling subject, the ranging sensor can measure the distance to different body parts of the subject, i.e., determine the position of different body parts of the subject relative to, for example, the ranging sensor. A range map can be constructed from the ranging data that can identify different body parts of the subject.

[0020] Therefore, measurement data including the positions for different body parts of the subject can be used to obtain curves representing the motion trajectories of specific body parts, including the head, of the subject. The motion trajectories at each instant of the fall event, animated over time, form the animated fall trajectory of the subject.

[0021] The subject's animated fall trajectory, set against a floor map containing the spatial location and dimensions of at least one fixed object in the space where the fall occurs, allows caregivers or medical staff to see in a straightforward manner whether the subject's head is performing an action that could cause a head injury.

[0022] In one example of the present disclosure, the step of generating an indication to assist in assessing a head injury based on the measurement data further comprises: - generating, based on the measurement data, distance data between the subject's head and at least one fixed object in the space in which the fall occurs during the fall event, based on the position of the subject's head and the spatial location of the at least one fixed object; Includes:

[0023] Using the distance of the subject's head at each moment during the fall event available from the measurement data and a floor map containing one or more fixed objects in the space in which the fall occurs, distance data between the subject's head and at least one fixed object is generated by calculating the distance between the subject's head and each of the at least one fixed object for each time instance with reference to a pre-generated floor map containing the spatial location and dimensions of the at least one fixed object.

[0024] This distance data between the subject's head and one or more fixed objects in the space where the fall occurs is also used together to assist in assessing the severity of head injury caused by the fall event. By combining different indicators, injuries resulting from a fall event can be objectively assessed, resulting in more reliable assessment results.

[0025] In one example of the present disclosure, the pre-generated three-dimensional floor map is obtained by measuring distance data of objects in the space where the fall occurs using a distance sensor.

[0026] The same ranging sensors used to acquire measurement data for fall events may also be used to map the space being monitored for potential falls in order to pre-generate a floor map, which includes fixed objects in the space, such as a sink or toilet in a bathroom.

[0027] In one example of the present disclosure, the method further includes rendering an indication on a display device to assist in assessing the head injury.

[0028] Those skilled in the art can envision that the generated indications to assist in the assessment of a head injury may be provided to interested parties, such as medical staff or caregivers, allowing them to use the indications in any manner they prefer.

[0029] On the other hand, the methods of the present disclosure may cause a display device, communicatively coupled or connected to a processor for executing the methods of the present disclosure, to render or display such indications to assist in the assessment of the head injury, which is particularly useful when the processor and display device are combined into a single device, allowing for more efficient display of the indications and allowing for immediate assessment of the head injury without delay after the relevant person notices the fall event.

[0030] In one example of the present disclosure, the method further comprises: - 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; - highlighting a point on the animated tipping trajectory that has a minimum distance to the fixed object of the at least one fixed object if the minimum distance to the fixed object of the at least one fixed object is less than a threshold; Includes:

[0031] Those skilled in the art can envision that the distance between a subject's head and a part of a fixed object represents, in a sense, an objective criterion for determining whether the subject's head has struck an object, which is independent of subjective impressions and is therefore a clear indicator of whether the head has struck something, and is a well-founded factor to be taken into account when assessing the possibility of head injury.

[0032] It is also possible that the head may strike an object, bounce up, and then strike an object again one or more times. Highlighting the point(s) in the animated fall trajectory where the distance between the subject's head and at least one fixed object is less than a threshold can help draw the attention of personnel to such points, enabling them to more quickly and reliably assess head injury.

[0033] In one example of the present disclosure, the method further comprises: - highlighting the subject's head velocity at instances corresponding to the highlighted points on the animated fall trajectory; Includes:

[0034] In addition to considering the distance between the subject's head and a fixed object in space where the fall occurs, the velocity of the head may also be considered. By highlighting the head velocity for the point(s) where the distance between the subject's head and a fixed object is highlighted, a more accurate assessment can be made as to whether the head actually struck an object.

[0035] In one example of the present disclosure, the method further comprises: - highlighting the distance between the subject's head and the fixed object at instances corresponding to the highlighted points on the animated fall trajectory; Includes:

[0036] If 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 the point highlighted on the animated fall trajectory.

[0037] When the animated fall trajectory, the subject's head velocity, and the distance of the subject's head relative to a fixed object are considered together, a more accurate assessment of the severity of the head injury caused by the fall event can be made.

[0038] In one example of the present disclosure, the ranging sensor includes a Time of Flight (ToF) sensor.

[0039] ToF sensors, especially low-resolution ToF sensors that are readily available on the market, are suitable for performing the measurements required in this disclosure, which helps keep the cost of the solution low.

[0040] A second aspect of the present disclosure provides a computing device including a processor, the processor configured to execute a method for assisting in the assessment of a head injury in a subject caused by a fall event occurring to the subject according to any of the first aspects of the present disclosure.

[0041] In one example of the present disclosure, the computing device includes a lighting device including an integrated ranging sensor and a processor; The ranging sensor is configured to obtain measurement data of the fall event over a period of time that includes the fall event.

[0042] An example of a computing device may be an intelligent light device that is currently deployed in many homes, where a ranging sensor can be conveniently integrated into the light device, reducing costs and saving space.

[0043] In one example of the present disclosure, the ranging sensor is further configured to obtain measurement data for pre-generating a floor map including the spatial location and dimensions of at least one fixed object in the space in which the fall occurs.

[0044] The floor map is generated based on the measurement data obtained by the ranging sensor by a processor, which may be included in the ranging sensor itself or in a device separate from the ranging sensor, depending on the computing power of the device including the processor.

[0045] In a further example of the present disclosure, the ranging sensor is a Time of Flight (ToF) sensor.

[0046] A third aspect of the present disclosure provides a computer program product including a computer-readable storage medium storing instructions that, when executed on at least one processor, cause the at least one processor to perform a method according to the first aspect of the present disclosure.

[0047] The above and other features and advantages of the present disclosure will be best understood from the following description taken in conjunction with the accompanying drawings, in which like reference numerals indicate identical parts or parts that perform the same or equivalent functions or operations. [Brief explanation of the drawings]

[0048] [Figure 1] FIG. 1 illustrates a schematic diagram of a fall detection system according to one embodiment of the present disclosure. [Figure 2] 2(a) to 2(c) respectively show a photo of a bathroom, distance measurement data of the bathroom, and a 3D floor map constructed from the distance measurement data. [Figure 3] FIG. 3 illustrates, in a flow chart type diagram, one embodiment of a method for assisting in the assessment of a subject's head injury caused by a fall event occurring to the subject according to the present disclosure. [Figure 4] 4(a)-4(e) show several snapshots of a fallback animation in chronological order according to the present disclosure. [Figure 5] FIG. 5 schematically illustrates exemplary head movement speeds and head distances relative to the toilet bowl during a tipping procedure according to the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0049] 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 limited to only the embodiments set forth herein. Rather, the illustrated embodiments are provided as examples to convey the scope of the subject matter to those skilled in the art.

[0050] Throughout this description, the terms "target," "user," "person," and "subject" are used interchangeably.

[0051] Described below are methods and computing devices (e.g., a backend server in communication with a fall detection device or a lighting device with fall detection capabilities) for assisting in the assessment of a subject's head injury caused by a fall event occurring to the subject.

[0052] The method for assisting head injury assessment proposed by the present disclosure is implemented using a fall detection system based on a ranging sensor, which may be a time-of-flight sensor, particularly a low-resolution ToF sensor, which may help keep the cost of the disclosed solution low.

[0053] 1 illustrates a schematic diagram of a fall detection system 10 according to one embodiment of the present disclosure. The fall detection system includes two main parts or components: one or more ranging sensors 11 and a computing or processing device or processor 12.

[0054] The ranging sensor 11 may be a low-resolution, e.g., 64-zone ToF sensor. The ToF sensor 11 may be installed on the ceiling of a space to be monitored, such as a restroom. The ToF sensor 11 is configured to monitor a target in space by capturing ranging data of the target in real time without capturing privacy information. If the target is a person, such ranging data may indicate the position and posture of the person. If the target is a fixed object, the ranging data may indicate the spatial location and dimensions of the object.

[0055] The computing or processing device or processor 12 may be a back-end server that is located remotely from the sensors 11. In this case, the processor 12 and each sensor 11 communicate with each other (19) over a network, such as the Internet 18, either wired or wirelessly.

[0056] The processor 12 is configured to receive data acquired or captured by the one or more sensors 11 and to store and optionally render such measured data. The processor may further be configured to determine, based on the data obtained from the sensors 11, whether a fall event is occurring or has occurred to the user.

[0057] The processor 12 may also be configured to trigger the alarm device 13, for example by a trigger message being sent (17) to the alarm device 13 when a fall event is detected.

[0058] The processor 12 has been described above as a separate or independent device from the sensor 11. However, as can be envisioned by one skilled in the art, the processor 12 and the sensor may be a single integrated device.

[0059] As an example, the sensor 11 may include a sensing portion and further have a built-in processor that may process raw data captured by the sensing portion of the sensor to determine possible events occurring to the user.

[0060] The sensor may also have an on-board or separate local processor for fall detection, and another processor at the back end or remote location for generating indications for injury assessment assistance.

[0061] The processor 12 has been described above as being located remotely from the sensor 11. In practice, the processor 12 may be located locally and communicatively connected to the sensor 11.

[0062] A particular example of a fall detection system contemplated by the present disclosure may be a lighting device that integrates a ranging sensor, such as a ToF sensor, and a processor. Such a lighting device may function as a fall detection device or system in addition to its lighting function. The lighting device may also perform the methods of the present disclosure, as detailed below, if sufficient computing resources are available to the lighting device.

[0063] As an example, the ToF sensor may be based on indoor lighting fixtures that are readily available in every home, such as LED lights fixed to the ceiling.

[0064] When the space in which the ToF sensor 11 is deployed is empty, the sensor 11 is configured to acquire measurement data of the space and send the measurements to the processor 12 to construct a three-dimensional (3D) floor map of the space. Such a 3D floor map includes the dimensions and positions of fixed objects in the space. As an example, if the space is a bathroom, fixed objects such as the toilet bowl and sink may be depicted on the 3D floor map.

[0065] 2(a) to 2(c) show a photo of the bathroom, distance measurement data of the bathroom, and a 3D floor map of the bathroom constructed from the distance measurement data, respectively. The distance measurement data is obtained using, for example, a ToF distance measurement sensor with 64 (8x8) zones.

[0066] Referring to Figure 2(b), such a ToF sensor can simultaneously output 64 range measurements (zone 1 to zone 64) in one frame, i.e., the distance from any object within the detection range to the sensor. The measurement frequency of a ToF sensor can range from a few frames per second (FPS) to several tens of FPS.

[0067] Specifically, FIG. 2(a) is a photograph 21 of a portion of an empty restroom, including a sink 22 and a toilet 23.

[0068] Figure 2(b) shows one frame output 24 of a 64-zone ToF sensor mounted on the ceiling of a bathroom. The sensor's field of view (FoV) covers the toilet bowl 23 and part of the sink 22.

[0069] Figure 2(c) is a 3D floor map 25 generated by a computing device, such as a back-end computing device, using the data of Figure 2(b) obtained by the ToF sensor. From the 3D floor map 25, the dimensions and positions of the fixed objects in the bathroom, namely the toilet bowl 23 and the sink 22, can be known. In fact, it is not necessary to know exactly what the fixed objects are.

[0070] The sink 22 and toilet 23 are shown in Figures 2(b) and 2(c).

[0071] FIG. 3 illustrates, in a flow chart type diagram, one embodiment of a method 30 for assisting in the assessment of a subject's head injury caused by a fall event occurring to the subject according to the present disclosure.

[0072] The above-mentioned 3D floor map of the space in which the fall event occurs is pre-generated by a computing device that executes the method for assisting in head injury assessment. Alternatively, such a 3D floor may be obtained from a further device that pre-generated the 3D floor map.

[0073] In step 31, if a fall event is detected by the fall detection system, the computing device or processor executing the method of the present disclosure obtains measurement data of the fall event occurring to a subject or user of the fall detection system, the measurement data continuing for a period of time that includes the fall event.

[0074] In practice, when a person is present in a space where a ToF sensor is deployed, the ToF sensor begins to monitor the person's movements and posture, and the sensor continues to record measurement data over a predefined period, such as the past 20 seconds.

[0075] Optionally, to reduce the size of the recorded data, the sensor may only record measurements of the zones that cover the person. The number of zones that cover a person is not fixed. If a person is standing or sitting, the person may occupy up to 8 zones. If a person is lying down or on the floor, the person may occupy up to 12 zones.

[0076] If a person falls, a fall detection system including a ToF sensor can detect the fall immediately after the person's body hits the floor. Fall detection is beyond the scope of this disclosure and will not be discussed herein.

[0077] At the moment a fall is detected, the recorded data includes measurement data covering the complete fall process experienced by the person. The ToF sensor then stops recording the measurement data and can send the recorded measurement data, optionally together with a fall alarm, to a computing device that executes a method for assisting in the assessment of head injuries, such as a back-end server.

[0078] As mentioned above, for each time instant, the measurement data includes ranging data or distances (from the ToF sensor) to different body parts of the subject.

[0079] In step 32, an indication to assist in the assessment of the head injury is generated based on the measurement data.

[0080] The indications to assist in the assessment of the head injury may be generated and provided to a user, allowing the user to display the indications in an appropriate manner, or, if a computing device including a processor for performing the methods of the present disclosure is equipped with or communicatively connected to a display device, the indications may be rendered or displayed directly on the display device in step 33.

[0081] As an example, an animated fall trajectory of the subject's head during the fall procedure may be rendered on a display device, along with the velocity of the subject's head and, optionally, the distance between the subject's head and one or more fixed objects during the fall procedure (all of which are described below), allowing medical staff or caregivers to objectively and reliably assess the severity of the head injury.

[0082] The indications may include an animated fall trajectory of the subject's head during the fall event and within the space in which the fall occurs, and velocity data of the subject's head during the fall event.

[0083] The animated fall trajectory of the subject's head and the velocity of the subject's head may be generated in any order, and one need not be generated before the other.

[0084] For injury assessment purposes, it is important to know whether the person who fell struck their head on a fixed object, such as a toilet or sink, during the fall, and if so, how severely they struck their head.

[0085] The animated fall trajectory and subject's head velocity generated by the present disclosure can be used to determine whether such a hitting is present, thereby assisting in the assessment of the subject's head injury.

[0086] As an example, a back-end server acting as a computing device for executing the method of the present disclosure analyzes the recorded measurement data to generate a playback animation of the falling process.

[0087] As can be imagined by those skilled in the art, multiple distances to different body parts of the subject are recorded by the ToF sensor for each moment of the fall procedure. The distances of the subject's head are sequentially arranged from the earliest moment to the latest moment of the period including the fall event to form a curve representing the movement trajectory of the subject's head during the period including the fall event. When the curves obtained for different moments of the fall procedure are played back in an animated manner against a 3D floor map of the space where the fall occurs, the fall procedure can be visualized.

[0088] The motion trajectory of the person's head may be highlighted in the playback animation relative to the person's posture changes during the fall procedure. Figures 4(a)-4(e) show several snapshots of the fall playback animation in time sequence.

[0089] Referring to Figure 4(a), a straight line segment 41 represents a standing person, and a small dot 42 at the top end of the straight line segment 41 represents the person's head. A curve 43 formed by the small triangles 42 shown in each of Figures 4(b) to 4(e) shows the trajectory of the person's head during the complete falling process.

[0090] The curve 43 is plotted against a 3D floor map representing the space in which the fall event occurs, allowing possible causes of head injury, such as the head hitting an object, to be directly identified.

[0091] Figure 4(b) shows that the fall has just begun, as curve 43 indicates that the head has just begun to move downward. From curve 43 in Figure 4(c), it can be seen that the head is moving towards the toilet bowl 23 and is about to hit the toilet bowl 43. Figure 4(d) shows the point at which the head makes contact with the toilet bowl 23. Figure 4(e) is the end of the fall, with the person lying on the floor.

[0092] To further confirm whether the person's head hit the toilet bowl and the severity of the hit, the backend calculates the person's head movement velocity, which is used as a further indication to assist in assessing head injuries. Based on the animated fall trajectory and the head movement velocity of the fallen person, better assessment results can be obtained.

[0093] The measurement data may also be used to obtain the distance between the person's head and any fixed objects in the space where the fall event occurs, such as the top of a toilet bowl, which can be used as a further indication to assist in the assessment of head injuries.

[0094] Those skilled in the art will appreciate that the velocity of movement of a subject's head, as opposed to an object such as a toilet, is calculated by dividing the difference in distance between the head at a given moment and the previous moment by the difference in time between the given moment and the previous moment.

[0095] The distance data to the object is determined by using the measured distance data of the subject's head and the distance data of the object that has been previously measured when generating a 3D floor map of the space in which the fall occurs.

[0096] FIG. 5 shows a schematic representation of exemplary head movement speed and head distance relative to the toilet bowl during a tipping procedure.

[0097] In Figure 5, the horizontal axis is a frame index associated with time. As an example, if the FPS is 10, one frame is 0.1 seconds. The bottom row of Figure 5 is the vertical head movement speed in meters per second (m / s), and the top row of Figure 5 is the head distance to the top of the toilet bowl in centimeters (cm).

[0098] Figure 5 covers the entire fall process and has six dashed lines that indicate different points during the fall. The first line A in Figure 5 is the same point as Figure 4(b), when the fall has just begun, and Figure 5 reflects that the head's velocity is beginning to increase and the distance between the head and the toilet bowl 23 is beginning to decrease.

[0099] The second line B in Figure 5, the same as Figure 4(c), indicates the point at which the person's head is about to hit the toilet. At this point, the head velocity is at its maximum (~0.8 m / s), and immediately after that, the head velocity drops sharply from approximately 0.8 m / s to 0.3 m / s within 0.1 seconds, confirming that the head hit the toilet.

[0100] The head velocity before hitting the toilet bowl and the change in velocity upon hitting the bowl are important pieces of information for assessing the severity of the hit.

[0101] The third line C in Figure 5 is the same as Figure 4(d), which shows the point at which the person's head makes contact with the toilet bowl. After this point, the head velocity increases for a short period, reflecting the head bouncing off the surface of the toilet bowl.

[0102] Thereafter, the speed and distance continue to decrease until the point indicated by the fourth line D in Figure 5, at which point the person's head and upper body remain stable above the toilet bowl until the point indicated by the fifth line E in Figure 5.

[0103] From point E, the person's upper body begins to fall toward the floor and is completely lying on the floor at the sixth line F, the same point as in Figure 4(e). During this period, the head velocity increases again and then decreases, while the head distance further decreases and falls below zero, indicating that the head is lower than the top of the toilet bowl.

[0104] Head injuries are likely to be caused by the head striking an object. In the present disclosure, the fact that the head is striking an object can be indicated by multiple parameters or indicators obtained from measurement data. Such parameters or indicators include the distance between the head and the object, the velocity of the head when striking the object, and the change in velocity of the head before and after striking the object.

[0105] Another factor to consider is when the head strikes an object, then bounces off and strikes the object a second or third time as a collective result of different forces, such as gravity and the impact force between the head and the object.

[0106] When assessing a head injury caused to a subject based on the animated fall trajectory, the velocity of the subject's head, and the distance between the subject's head and one or more fixed objects, moments with a minimum distance between the subject's head and one or more fixed objects and / or moments with a significant change in velocity of the subject's head are considered relative to each other, thereby enabling a more accurate assessment of a possible head injury.

[0107] Information of particular interest to medical staff or caregivers may be highlighted to draw their attention to the displayed indications to assist in the assessment of the head injury. Therefore, in step 34, one or more of the rendered indications are highlighted.

[0108] As an example, one or more points on an animated trajectory of the subject's head having a minimum distance to each of at least one fixed object may be determined, and if the minimum distance to the fixed object of the at least one fixed object is less than a threshold value (e.g., 20 cm), the point on the animated trajectory having such distance is highlighted.

[0109] Additionally, not only the subject's head but also the distance between the subject and the fixed object at or around the time the subject struck the object may be highlighted, as shown by the gray area in Figure 5. This further assists medical staff or caregivers in quickly and accurately assessing the subject's head injury.

[0110] Those skilled in the art can envision that the assessment results, along with 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, may be rendered to medical staff or caregivers, allowing them to assess the overall situation based on their professional experience.

[0111] The present disclosure is not limited to the examples disclosed above, but can be modified and extended by those skilled in the art beyond the scope of the present disclosure disclosed in the appended claims without the need to apply inventive skills, for use in any data communication, data exchange and data processing environment, system or network.

Claims

1. 1. A method for assisting in the assessment of a head injury in a subject caused by a fall event occurring to the subject, the method being executed by a processor and comprising: Upon detection of a fall event, obtaining measurement data of the fall event over a period of time including the fall event; generating an indication based on the measurement data to assist in assessing a head injury; Including, The indication is An animated fall trajectory of the subject's head during the fall event and within the space in which the fall occurs; and Velocity data of the subject's head during the fall event; Including, generating an indication to assist in assessing a head injury based on the measurement data, generating, based on the measurement data, distance data between the subject's head and at least one fixed object in the space where the fall occurs during a fall event, based on the position of the subject's head and the spatial location of the at least one fixed object; A method comprising:

2. The method of claim 1 , wherein the measurement data of a fall event is obtained by measuring, with a ranging sensor, distance data of different body parts of the subject over multiple moments in the period that includes the fall event.

3. The ranging data at each instant of the time period includes a plurality of positions of different body parts of the subject, and the animated fall trajectory of the subject is calculated by: sequentially arranging the positions of the subject's head from the earliest moment to the latest moment during the period including the fall event to obtain a curve representing a movement trajectory of the subject's head during the period including the fall event; setting said curve against a pre-generated three-dimensional floor map including the spatial location and dimensions of at least one fixed object in said space where a fall will occur; The method of claim 2, wherein the compound is produced by

4. The method of claim 3 , wherein the pre-generated three-dimensional floor map is obtained by measuring, with the ranging sensor, ranging data of objects in the space where a fall occurs.

5. 5. The method of claim 1, further comprising rendering the indication to assist in assessment of a head injury on a display device.

6. The method comprises: finding one or more points on the animated fall trajectory of the subject's head that have a minimum distance to each of the at least one fixed object; highlighting a point on the animated tumble trajectory that has a minimum distance to a fixed object of the at least one fixed object if the minimum distance to the fixed object of the at least one fixed object is less than a threshold; The method of claim 5 , comprising:

7. The method comprises: highlighting the subject's head velocity at instances corresponding to the highlighted points on the animated fall trajectory; The method of claim 6, comprising:

8. The method comprises: highlighting the distance between the subject's head and the fixed object at the instance corresponding to the highlighted point on the animated fall trajectory; 8. The method of claim 6 or 7, comprising:

9. The method according to any one of claims 1 to 8, wherein the ranging sensor is a Time of Flight (ToF) sensor.

10. 10. A computing device including a processor, the processor configured to execute a method for assisting in the assessment of a head injury in a subject caused by a fall event occurring to the subject, as described in any one of claims 1 to 9.

11. the computing device includes an illumination device including an integrated ranging sensor and the processor; The computing device of claim 10 , wherein the ranging sensor is configured to obtain measurement data of a fall event over a period of time that includes the fall event.

12. 12. The computing device of claim 11, wherein the ranging sensor is configured to obtain measurement data for pre-generating a floor map including spatial locations and dimensions of at least one fixed object in a space in which a fall occurs.

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

14. 10. A computer program product comprising a computer readable storage medium having stored thereon instructions which, when executed on at least one processor, cause said at least one processor to perform the method of any one of claims 1 to 9.

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