Self-adaptive hand tremor assessment method, assessment device and readable storage medium

Abstract

The invention discloses a self-adaptive hand tremor evaluation method and device and a storage medium, and belongs to the technical field of tremor evaluation. Comprising the steps of obtaining a current hand video of a hand of a tested person, and determining current tremor intensity of the hand of the tested person and a current shooting influence factor of current shooting of the tested person based on the current hand video; an initial hand video of the hand of the tested person at a preset time before the current time is obtained, an initial shooting influence factor for initial shooting of the tested person is determined based on the initial hand video, and the initial shooting influence factor represents an initial conversion coefficient between a hand pixel point in the initial hand video and the actual distance; based on the current tremor intensity, the current shooting influence factor and the initial shooting influence factor, the real tremor amplitude of the hand of the tested person is determined, and the real tremor amplitude is evaluated.

Description

Technical Field

[0001] This application belongs to the field of tremor assessment technology, specifically relating to an adaptive hand tremor assessment method, assessment device, and readable storage medium. Background Technology

[0002] Tremor is one of the most common signs of movement disorders, widely seen in essential tremor, Parkinson's disease, cerebellar lesions, and syndromes caused by drug / metabolic factors. Clinical assessment has traditionally relied on visual observation and scales, but these methods are highly subjective, lack interdisciplinary consistency, and have limited longitudinal comparability. This results in low reliability of tremor assessment results for individuals being tested. Summary of the Invention

[0003] This application aims to provide an adaptive method, device, and readable storage medium for assessing hand tremors, at least addressing the problem of low reliability of tremor assessment results for test subjects.

[0004] To solve the above-mentioned technical problems, this application is implemented as follows: In a first aspect, embodiments of this application propose an adaptive hand tremor assessment method, the adaptive hand tremor assessment method comprising: The current hand video of the subject is acquired, and based on the current hand video, the current tremor intensity of the subject's hand and the current shooting influence factor for the subject's current shooting are determined. The current tremor intensity is the tremor intensity that is independent of the distance between the shooting device and the subject, and the current shooting influence factor represents the current conversion coefficient between the pixel points of the hand in the current hand video and the actual distance. Acquire an initial hand video of the subject at a preset time prior to the current time, and based on the initial hand video, determine an initial shooting influence factor for the initial shooting of the subject. The initial shooting influence factor represents the initial conversion coefficient between the hand pixels in the initial hand video and the actual distance. Based on the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, the true tremor amplitude of the subject's hand is determined, and the true tremor amplitude is evaluated.

[0005] Optionally, determining the current tremor intensity of the subject's hand based on the current hand video includes: In the current hand video, a region of interest is determined, which is the area including the palm of the subject's hand; Determine the motion sequence of the region of interest, and filter the motion sequence; Based on the filtered motion sequence, the current tremor intensity of the subject's hand is determined.

[0006] Optionally, determining the current shooting influence factor based on the current hand video for the subject includes: In the current hand video, determine the short window where the subject's hand is in a resting state or in a standard posture, and determine the palm width and fingertip span of the subject's hand, and determine the monocular depth for the current hand video; In the current hand video, residual tremor noise of the subject's hand in a resting state is determined; Based on the short window, palm width, fingertip span, monocular depth, and residual tremor noise, the current shooting influence factor for the current shooting of the subject is determined.

[0007] Optionally, the adaptive hand tremor assessment method further includes: Update the current shooting impact factor; The process of determining the true tremor amplitude of the subject's hand based on the current tremor intensity, the current imaging impact factor, and the initial imaging impact factor includes: Based on the current tremor intensity, the updated current shooting influence factor, and the initial shooting influence factor, the actual tremor amplitude of the subject's hand is determined, and the updated current shooting influence factor is used to determine the current shooting influence factor.

[0008] Optionally, determining the initial shooting influence factor for the initial shooting of the subject based on the initial hand video includes: The main features of the subject's hand are extracted from the initial hand video, wherein the initial hand video contains videos of the subject performing at least two standard postures; Based on the aforementioned key features, an initial shooting influence factor is generated for the initial shooting of the subject.

[0009] Optionally, the adaptive hand tremor assessment method further includes: If an alignment sample with a physical scale exists, then the initial shooting influence factor is calibrated according to the alignment sample; The process of determining the true tremor amplitude of the subject's hand based on the current tremor intensity, the current imaging impact factor, and the initial imaging impact factor includes: Based on the current tremor intensity, the current shooting influence factor, and the calibrated initial shooting influence factor, the current shooting influence factor after updating the actual tremor amplitude of the subject's hand is determined.

[0010] Optionally, the adaptive hand tremor assessment method further includes: Generate a tremor assessment report for the subject, the tremor assessment report including at least one of the tremor frequency and tremor amplitude for the subject.

[0011] Optionally, determining the true tremor amplitude of the subject's hand based on the current tremor intensity, the current imaging influence factor, and the initial imaging influence factor includes: The product of the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor is taken as the true tremor amplitude of the subject's hand.

[0012] Secondly, embodiments of this application provide an evaluation apparatus, the evaluation apparatus comprising: The first acquisition module is used to acquire the current hand video of the subject's hand, and based on the current hand video, determine the current tremor intensity of the subject's hand and the current shooting influence factor for the subject's current shooting. The current tremor intensity is the tremor intensity that is independent of the distance between the shooting device and the subject, and the current shooting influence factor represents the current conversion coefficient between the pixel points of the hand in the current hand video and the actual distance. The second acquisition module is used to acquire an initial hand video of the subject's hand at a preset time before the current time, and based on the initial hand video, determine an initial shooting influence factor for the initial shooting of the subject. The initial shooting influence factor represents the initial conversion coefficient between the hand pixels in the initial hand video and the actual distance. The determination module is used to determine the true tremor amplitude of the subject's hand based on the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, and to evaluate the true tremor amplitude.

[0013] Optionally, the first acquisition module includes: The first determining submodule is used to determine a region of interest in the current hand video, wherein the region of interest is the area including the palm of the person being tested; The second determining submodule is used to determine the motion sequence of the region of interest and to filter the motion sequence; The third determining submodule is used to determine the current tremor intensity of the subject's hand based on the filtered motion sequence.

[0014] Optionally, the first acquisition module includes: The fourth determination submodule is used to determine, in the current hand video, whether the test subject's hand is in a resting state or the hand is in a standard posture, a short window, and to determine the palm width and fingertip span of the test subject's hand, and to determine the monocular depth for the current hand video. The fifth determining submodule is used to determine, in the current hand video, the residual tremor noise of the subject's hand in a resting state; The sixth determination submodule is used to determine the current shooting influence factor for the subject being photographed based on the short window, the palm width, the fingertip span, the monocular depth, and the residual tremor noise.

[0015] Optionally, the evaluation apparatus further includes: The update module updates the current shooting impact factor; The first acquisition module is also used for: Based on the current tremor intensity, the updated current shooting influence factor, and the initial shooting influence factor, the actual tremor amplitude of the subject's hand is determined, and the updated current shooting influence factor is used to determine the current shooting influence factor.

[0016] Optionally, the second acquisition module includes: An extraction submodule is used to extract the main features of the subject's hand from the initial hand video, wherein the initial hand video contains videos of the subject performing at least two standard poses; A generation submodule is used to generate an initial shooting influence factor for the initial shooting of the subject based on the main features.

[0017] Optionally, the evaluation apparatus further includes: The calibration module is used to calibrate the initial imaging influence factor according to the alignment sample if an alignment sample with a physical scale exists. The second acquisition module is further configured to: Based on the current tremor intensity, the current shooting influence factor, and the calibrated initial shooting influence factor, the current shooting influence factor after updating the actual tremor amplitude of the subject's hand is determined.

[0018] Optionally, the evaluation apparatus further includes: A generation module is used to generate a tremor assessment report for the subject, the tremor assessment report including at least one of the tremor frequency and tremor amplitude for the subject.

[0019] Optionally, the determining module is further configured to: The product of the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor is taken as the true tremor amplitude of the subject's hand.

[0020] Thirdly, embodiments of this application provide an electronic device including a processor and a memory, wherein the memory stores programs or instructions executable on the processor, and the programs or instructions, when executed by the processor, implement the steps of the method described in the first aspect.

[0021] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0022] Fifthly, embodiments of this application provide a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the method as described in the first aspect.

[0023] In a sixth aspect, embodiments of this application provide a computer program product stored in a storage medium, which is executed by at least one processor to implement the method described in the first aspect.

[0024] In this embodiment, a current hand video of the subject is acquired, and based on this video, the current tremor intensity and the current shooting influence factor for the subject's current shooting are determined. An initial hand video of the subject's hand taken at a preset time prior to the current time is acquired, and based on this initial video, the initial shooting influence factor for the subject's initial shooting is determined. Based on the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, the true tremor amplitude of the subject's hand is determined, and an evaluation is performed on the true tremor amplitude. That is, in this embodiment, the true tremor intensity of the subject's hand is determined by the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, effectively separating tremor intensity, differences in shooting environment, and individual differences, making it easier to control errors. Furthermore, based on data such as the current shooting influence factor and the initial shooting influence factor, it can be determined whether the change in tremor stems from the subject's condition or the shooting conditions, effectively improving the reliability of the tremor assessment for the subject. Attached Figure Description

[0025] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a flowchart illustrating an adaptive hand tremor assessment method provided in an embodiment of this application; Figure 2 This diagram illustrates an evaluation apparatus provided in an embodiment of this application. Figure 3 This diagram illustrates an electronic device provided in an embodiment of this application. Figure 4 This is a schematic diagram illustrating the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0026] The embodiments of this application will now be described in detail. Examples of these embodiments are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0027] The terms "first" and "second" in the specification and claims of this application may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise stated, "multiple" means two or more. Furthermore, "and / or" in the specification and claims indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0028] This application provides an adaptive method for assessing hand tremor, such as... Figure 1 As shown, this adaptive hand tremor assessment method includes: Step 101: Obtain the current hand video of the subject and, based on the current hand video, determine the current tremor intensity of the subject's hand and the current shooting influence factor for the subject's current shooting. The current tremor intensity is the tremor intensity that is independent of the distance between the shooting device and the subject, and the current shooting influence factor represents the current conversion coefficient between the pixel points of the hand in the current hand video and the actual distance.

[0029] The hand video can be captured by an electronic device capable of recording video, including but not limited to mobile phones, cameras, and tablets. Furthermore, in this embodiment, when it is necessary to assess or detect tremors in the hands of the test subject, the subject's hands can be filmed, resulting in a current hand video. Alternatively, the upper body or full body of the test subject can be filmed, as long as the video includes the hands, thus obtaining a equivalent current hand video.

[0030] It should be noted that the current vibration intensity is independent of the distance between the imaging device and the person being tested, meaning that the current vibration intensity remains unchanged regardless of how the distance between the imaging device and the person being tested changes.

[0031] In addition, in some implementations, the method to determine the current tremor intensity of the subject's hand based on the current hand video can be as follows: determine the region of interest in the current hand video, which is the area including the subject's palm; determine the motion sequence of the region of interest and filter the motion sequence; and determine the current tremor intensity of the subject's hand based on the filtered motion sequence.

[0032] The area of ​​interest is the area that includes the palm of the test subject, or the area of ​​interest includes key points on the palm of the test subject, such as the fingertips and wrist.

[0033] In addition, hand videos are essentially multiple image frames, which is equivalent to determining the region of interest from multiple image frames. The determined region of interest is also an image frame that changes over time. Therefore, the motion sequence of the region of interest is the motion sequence of key points trembling over time.

[0034] For example, the motion sequence of the region of interest can be denoted as... .

[0035] Additionally, when filtering motion sequences, the following formula can be used for calculation:

[0036] in Initialized on the vibration band, the frequency of which is 6Hz–12Hz.

[0037] In addition, the following formula can be used to determine the current tremor intensity of the subject's hand based on the filtered motion sequence:

[0038] The relative amplitude is obtained by RMS convergence of the envelopes of each channel:

[0039] Where Arel(t) represents the current intensity of hand tremor.

[0040] Additionally, some implementations can process the current hand video after it is acquired to suppress the effects of camera shake. Specifically, this involves creating a hand skeleton diagram. With the wrist as the root node and edges connecting to the palm and finger joints, the cross-spectrum and coherence of the displacement sequence of each edge with the wrist can be calculated.

[0041] By analyzing the vibration frequency band Applying loss:

[0042] Where W represents the wrist node, i represents the index of a node in the skeleton graph, f represents the frequency, x_i(t) represents the motion sequence (time series of displacement / velocity / acceleration) of node i, x_w(t) represents the motion sequence of wrist node w, and S xi xw (f) represents x i With x w The cross-power spectral density, usually a complex number, reflects the common components and phase relationship of the two signals in the frequency domain. xi xi (f) represents x i The self-power spectral density, Sxwxw(f) represents x w The self-power spectral density.

[0043] Then, by using wrist coordinates and common mode decomposition, all translation components are deducted from the fingertip displacement, thus suppressing the impact of camera / camera shake.

[0044] In addition, in some implementations, the method for determining the current shooting influence factor for the subject based on the current hand video can be as follows: In the current hand video, determine the short window where the subject's hand is in a resting state or in a standard posture, and determine the palm width and fingertip span of the subject's hand, and determine the monocular depth for the current hand video; In the current hand video, determine the residual tremor noise of the subject's hand in a resting state; Based on the short window, palm width, fingertip span, monocular depth, and residual tremor noise, determine the current shooting influence factor for the subject.

[0045] The current hand video includes frames showing the subject at rest and frames showing the subject's hand in a standard posture. The standard posture can be the subject's hand extended horizontally in front of them with their palm facing down.

[0046] In addition, monocular depth refers to estimating depth information using only a single viewpoint image captured by a single camera. This involves calculating the distance from each pixel in the scene to the camera and outputting a depth map of the same size as the input image, where pixel values ​​represent the distance at that location. Typically, this is represented in grayscale or pseudo-color, with brighter / darker colors corresponding to closer / farder distances.

[0047] In addition, based on the short window, palm width, fingertip span, monocular depth, and residual tremor noise, the following formula can be used to determine the current shooting influence factor for the subject's current shooting:

[0048] Among them, the palm width is Fingertip span is Monocular depth is The residual flutter noise is , This represents the current shooting impact factor.

[0049] Step 102: Obtain the initial hand video of the subject at a preset time before the current time, and based on the initial hand video, determine the initial shooting influence factor for the initial shooting of the subject. The initial shooting influence factor represents the initial conversion coefficient between the hand pixels in the initial hand video and the actual distance.

[0050] The hand video can be captured by an electronic device capable of recording video, including but not limited to mobile phones, cameras, and tablets. Furthermore, in this embodiment, the subject's hand can be filmed at a preset time prior to the current time to obtain an initial hand video, which can then be stored and retrieved directly when needed.

[0051] It should be noted that the preset time can be set according to actual needs. For example, the hands of the test subject can be filmed one month before the current time to obtain the initial hand video.

[0052] Furthermore, the duration of the initial hand video can be determined according to actual needs, and can be greater than or equal to 30 seconds. For example, the duration of the initial hand video is 45 seconds, or even 60 seconds. This application does not limit the specific duration of the video.

[0053] In addition, in some implementations, the method of determining the initial shooting influence factor for the initial shooting of the test subject based on the initial hand video can be as follows: extract the main features of the test subject's hand from the initial hand video, wherein the initial hand video contains videos of the test subject performing at least two standard poses; and generate the initial shooting influence factor for the initial shooting of the test subject based on the main features.

[0054] The standard posture is for the subject to extend their hands horizontally in front of their body with their palms facing down.

[0055] In addition, the main features can be used If so, the main features can be extracted as shown in the following formula:

[0056] In addition, the following formula can be used to generate the initial shooting influence factor for the initial shooting of the test subject based on the main features:

[0057] in, This represents the initial shooting impact factor. The formula means that the "subject's main features" c_s are input into a parameterized mapping function / model g_{\psi}(\cdot), and the output is the subject's "initial shooting impact factor" S_{\text{subject}}. In other words, a model is used to estimate an individual-related scaling / correction coefficient based on the subject's features in the initial hand video.

[0058] Step 103: Based on the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, determine the true tremor amplitude of the subject's hand and evaluate the true tremor amplitude.

[0059] Specifically, by using the current tremor intensity, current imaging influence factor, and initial imaging influence factor, the true tremor intensity of the subject's hand can be determined. This effectively separates tremor intensity from differences in imaging environment and individual differences, making it easier to control errors. Furthermore, based on data such as the current imaging influence factor and the initial imaging influence factor, it can be determined whether the change in tremor stems from the subject's condition or imaging conditions, thus effectively improving the reliability of tremor assessments for the subject.

[0060] In some implementations, step 103 can be implemented by multiplying the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, and using the product as the true tremor amplitude of the subject's hand.

[0061] Specifically, the calculation of the actual tremor amplitude can be referenced by the following formula:

[0062] Among them, A final (t) represents the true amplitude of the tremor.

[0063] In addition, in some implementations, the adaptive hand tremor assessment method further includes: updating the current shooting influence factor; then step 103 can be implemented as follows: based on the current tremor intensity, the updated current shooting influence factor, and the initial shooting influence factor, determine the actual tremor amplitude of the subject's hand and update the current shooting influence factor.

[0064] After determining the current shooting impact factor, the inference phase introduces an exponential sliding update, as shown in the following formula:

[0065] Then, the true tremor amplitude of the subject's hand can be determined by the current tremor intensity, the updated current shooting influence factor, and the initial shooting influence factor.

[0066] In addition, in some implementations, the adaptive hand tremor assessment method further includes: if there is an aligned sample with a physical scale, then the initial shooting influence factor is calibrated according to the aligned sample; then step 103 can be implemented as follows: based on the current tremor intensity, the current shooting influence factor, and the calibrated initial shooting influence factor, the current shooting influence factor after updating the actual tremor amplitude of the subject's hand is determined.

[0067] The initial imaging impact factor is calibrated according to the aligned samples, as shown in the following formula:

[0068] Among them, the aligned sample is .

[0069] Then, based on the current tremor intensity, the current shooting influence factor, and the calibrated initial shooting influence factor, the actual tremor amplitude of the subject's hand can be determined and the updated current shooting influence factor can be used.

[0070] In addition, in some implementations, the adaptive hand tremor assessment method further includes: generating a tremor assessment report for the subject, the tremor assessment report including at least one of the subject's tremor frequency and tremor amplitude.

[0071] In this embodiment, a current hand video of the subject is acquired, and based on this video, the current tremor intensity and the current shooting influence factor for the subject's current shooting are determined. An initial hand video of the subject's hand taken at a preset time prior to the current time is acquired, and based on this initial video, the initial shooting influence factor for the subject's initial shooting is determined. Based on the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, the true tremor amplitude of the subject's hand is determined, and an evaluation is performed on the true tremor amplitude. That is, in this embodiment, the true tremor intensity of the subject's hand is determined by the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, effectively separating tremor intensity, differences in shooting environment, and individual differences, making it easier to control errors. Furthermore, based on data such as the current shooting influence factor and the initial shooting influence factor, it can be determined whether the change in tremor stems from the subject's condition or the shooting conditions, effectively improving the reliability of the tremor assessment for the subject.

[0072] The adaptive hand tremor assessment method provided in this application can be executed by an assessment device. This application uses an assessment device executing the adaptive hand tremor assessment method as an example to illustrate the assessment device provided in this application.

[0073] This application provides an evaluation device, such as... Figure 2 As shown, the evaluation device 200 includes: The first acquisition module 201 is used to acquire the current hand video of the subject's hand, and based on the current hand video, determine the current tremor intensity of the subject's hand and the current shooting influence factor for the subject's current shooting. The current tremor intensity is the tremor intensity that is independent of the distance between the shooting device and the subject, and the current shooting influence factor represents the current conversion coefficient between the pixel point of the hand in the current hand video and the actual distance. The second acquisition module 202 is used to acquire the initial hand video of the test subject at a preset time before the current time, and based on the initial hand video, determine the initial shooting influence factor for the initial shooting of the test subject. The initial shooting influence factor represents the initial conversion coefficient between the hand pixels in the initial hand video and the actual distance. The determination module 203 is used to determine the true tremor amplitude of the subject's hand based on the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, and to evaluate the true tremor amplitude.

[0074] Optionally, the first acquisition module includes: The first determination submodule is used to determine the region of interest in the current hand video, which is the area including the palm of the subject. The second determining submodule is used to determine the motion sequence of the region of interest and to filter the motion sequence; The third determination submodule is used to determine the current tremor intensity of the subject's hand based on the filtered motion sequence.

[0075] Optionally, the first acquisition module includes: The fourth determination submodule is used to determine, in the current hand video, whether the subject's hand is in a resting state or in a standard posture, the short window, the palm width and fingertip span of the subject's hand, and the monocular depth for the current hand video. The fifth determination submodule is used to determine the residual tremor noise of the subject's hand in a resting state in the current hand video; The sixth determination submodule is used to determine the current shooting influence factor for the subject based on the short window, palm width, fingertip span, monocular depth, and residual tremor noise.

[0076] Optionally, the evaluation device also includes: Update module, update the current shooting impact factor; The first acquisition module is also used for: Based on the current tremor intensity, the updated current shooting influence factor, and the initial shooting influence factor, the true tremor amplitude of the subject's hand is determined, and the updated current shooting influence factor is used to determine the current shooting influence factor.

[0077] Optionally, the second acquisition module includes: The extraction submodule is used to extract the main features of the subject's hand from the initial hand video, wherein the initial hand video contains videos of the subject performing at least two standard poses; The generation submodule is used to generate initial shooting influence factors for the initial shooting of the subject based on the main features.

[0078] Optionally, the evaluation device also includes: The calibration module is used to calibrate the initial imaging impact factor according to the aligned sample if an aligned sample with a physical scale exists. The second acquisition module is also used for: Based on the current tremor intensity, the current shooting influence factor, and the calibrated initial shooting influence factor, the current shooting influence factor after updating the actual tremor amplitude of the subject's hand is determined.

[0079] Optionally, the evaluation device also includes: The generation module is used to generate a tremor assessment report for the test subject, which includes at least one of the tremor frequency and tremor amplitude for the test subject.

[0080] Optionally, the determining module is also used for: Multiply the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, and the product is taken as the true tremor amplitude of the subject's hand.

[0081] In this embodiment, a current hand video of the subject is acquired, and based on this video, the current tremor intensity and the current shooting influence factor for the subject's current shooting are determined. An initial hand video of the subject's hand taken at a preset time prior to the current time is acquired, and based on this initial video, the initial shooting influence factor for the subject's initial shooting is determined. Based on the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, the true tremor amplitude of the subject's hand is determined, and an evaluation is performed on the true tremor amplitude. That is, in this embodiment, the true tremor intensity of the subject's hand is determined by the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, effectively separating tremor intensity, differences in shooting environment, and individual differences, making it easier to control errors. Furthermore, based on data such as the current shooting influence factor and the initial shooting influence factor, it can be determined whether the change in tremor stems from the subject's condition or the shooting conditions, effectively improving the reliability of the tremor assessment for the subject.

[0082] The evaluation device in this application embodiment can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the scope of the device.

[0083] The evaluation device in this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit the specific operating system used.

[0084] The evaluation apparatus provided in this application embodiment can achieve... Figure 1 The various processes implemented in the method implementation examples will not be described again here to avoid repetition.

[0085] Optionally, such as Figure 3 As shown, this application embodiment also provides an electronic device 100, including a processor 1101 and a memory 109. The memory 109 stores a program or instructions that can run on the processor 110. When the program or instructions are executed by the processor 110, they implement the various steps of the above-described adaptive hand tremor assessment method embodiment and can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0086] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0087] Figure 4 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of this application.

[0088] The electronic device 100 includes, but is not limited to, components such as: radio frequency unit 101, network module 102, audio output unit 103, input unit 104, sensor 105, display unit 106, user input unit 107, interface unit 108, memory 109, and processor 110.

[0089] Those skilled in the art will understand that the electronic device 100 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 110 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 4 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0090] The processor 110 is configured to: acquire a current hand video of the subject, and based on the current hand video, determine the current tremor intensity of the subject's hand and the current shooting influence factor for the current shooting of the subject, wherein the current tremor intensity is the tremor intensity independent of the distance between the shooting device and the subject, and the current shooting influence factor represents the current conversion coefficient between the pixel of the hand in the current hand video and the actual distance; acquire an initial hand video of the subject's hand at a preset time before the current time, and based on the initial hand video, determine the initial shooting influence factor for the initial shooting of the subject, wherein the initial shooting influence factor represents the initial conversion coefficient between the pixel of the hand in the initial hand video and the actual distance; and based on the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, determine the true tremor amplitude of the subject's hand, and evaluate the true tremor amplitude.

[0091] In this embodiment, a current hand video of the subject is acquired, and based on this video, the current tremor intensity and the current shooting influence factor for the subject's current shooting are determined. An initial hand video of the subject's hand taken at a preset time prior to the current time is acquired, and based on this initial video, the initial shooting influence factor for the subject's initial shooting is determined. Based on the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, the true tremor amplitude of the subject's hand is determined, and an evaluation is performed on the true tremor amplitude. That is, in this embodiment, the true tremor intensity of the subject's hand is determined by the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, effectively separating tremor intensity, differences in shooting environment, and individual differences, making it easier to control errors. Furthermore, based on data such as the current shooting influence factor and the initial shooting influence factor, it can be determined whether the change in tremor stems from the subject's condition or the shooting conditions, effectively improving the reliability of the tremor assessment for the subject.

[0092] Optionally, the processor 110 is further configured to: determine a region of interest in the current hand video, the region of interest being a region including the palm of the subject; determine a motion sequence of the region of interest and filter the motion sequence; and determine the current tremor intensity of the subject's hand based on the filtered motion sequence.

[0093] Optionally, the processor 110 is further configured to: determine, in the current hand video, a short window indicating whether the subject's hand is in a resting state or in a standard hand posture, and determine the palm width and finger span of the subject's hand, and determine the monocular depth for the current hand video; determine, in the current hand video, residual tremor noise when the subject's hand is in a resting state; and determine the current shooting influence factor for the subject's current shooting based on the short window, palm width, finger span, monocular depth, and residual tremor noise.

[0094] Optionally, the processor 110 is also configured to: update the current shooting influence factor; the processor 110 is also configured to: determine the actual tremor amplitude of the subject's hand and the updated current shooting influence factor based on the current tremor intensity, the updated current shooting influence factor, and the initial shooting influence factor.

[0095] Optionally, the processor 110 is further configured to: extract key features of the subject's hand from an initial hand video, wherein the initial hand video contains videos of the subject performing at least two standard poses; and generate an initial shooting influence factor for the initial shooting of the subject based on the key features.

[0096] Optionally, the processor 110 is further configured to: if an aligned sample with a physical scale exists, calibrate the initial shooting influence factor according to the aligned sample; the processor 110 is further configured to: determine the updated current shooting influence factor based on the current tremor intensity, the current shooting influence factor, and the calibrated initial shooting influence factor to determine the true tremor amplitude of the subject's hand.

[0097] Optionally, the processor 110 is also configured to: generate a tremor assessment report for the subject, the tremor assessment report including at least one of the subject's tremor frequency and tremor amplitude.

[0098] Optionally, the processor 110 is also configured to: multiply the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, and use the product as the true tremor amplitude of the subject's hand.

[0099] In this embodiment, a current hand video of the subject is acquired, and based on this video, the current tremor intensity and the current shooting influence factor for the subject's current shooting are determined. An initial hand video of the subject's hand taken at a preset time prior to the current time is acquired, and based on this initial video, the initial shooting influence factor for the subject's initial shooting is determined. Based on the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, the true tremor amplitude of the subject's hand is determined, and an evaluation is performed on the true tremor amplitude. That is, in this embodiment, the true tremor intensity of the subject's hand is determined by the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, effectively separating tremor intensity, differences in shooting environment, and individual differences, making it easier to control errors. Furthermore, based on data such as the current shooting influence factor and the initial shooting influence factor, it can be determined whether the change in tremor stems from the subject's condition or the shooting conditions, effectively improving the reliability of the tremor assessment for the subject.

[0100] It should be understood that, in this embodiment, the input unit 104 may include a graphics processing unit (GPU) 1041 and a microphone 1042. The GPU 1041 processes video data of still images or videos obtained by an image capture device (such as a camera) in video capture mode or image capture mode. The display unit 106 may include a display panel 1061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, or the like. The user input unit 107 includes at least one of a touch panel 1071 and other input devices 1072. The touch panel 1071 is also called a touch screen. The touch panel 1071 may include a touch detection device and a touch controller. Other input devices 1072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, and joysticks, which will not be described in detail here.

[0101] The memory 109 can be used to store software programs and various data. The memory 109 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 109 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 109 in the embodiments of this application includes, but is not limited to, these and any other suitable types of memory.

[0102] Processor 110 may include one or more processing units; optionally, processor 110 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into processor 110.

[0103] This application also provides a readable storage medium storing a program or instructions that, when executed by a processor, implement the various processes of the above-described adaptive hand tremor assessment method embodiment and achieve the same technical effect. To avoid repetition, these will not be described again here.

[0104] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0105] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described adaptive hand tremor assessment method embodiment and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0106] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0107] This application provides a computer program product stored in a storage medium. The program product is executed by at least one processor to implement the various processes of the adaptive hand tremor assessment method embodiment described above, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0108] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0109] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0110] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. An adaptive method for assessing hand tremor, characterized in that, The adaptive hand tremor assessment method includes: The current hand video of the subject is acquired, and based on the current hand video, the current tremor intensity of the subject's hand and the current shooting influence factor for the subject's current shooting are determined. The current tremor intensity is the tremor intensity that is independent of the distance between the shooting device and the subject, and the current shooting influence factor represents the current conversion coefficient between the pixel points of the hand in the current hand video and the actual distance. Acquire an initial hand video of the subject at a preset time prior to the current time, and based on the initial hand video, determine an initial shooting influence factor for the initial shooting of the subject. The initial shooting influence factor represents the initial conversion coefficient between the hand pixels in the initial hand video and the actual distance. Based on the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, the true tremor amplitude of the subject's hand is determined, and the true tremor amplitude is evaluated.

2. The adaptive hand tremor assessment method according to claim 1, characterized in that, Determining the current tremor intensity of the subject's hand based on the current hand video includes: In the current hand video, a region of interest is determined, which is the area including the palm of the subject's hand; Determine the motion sequence of the region of interest, and filter the motion sequence; Based on the filtered motion sequence, the current tremor intensity of the subject's hand is determined.

3. The adaptive hand tremor assessment method according to claim 1, characterized in that, The step of determining the current shooting influence factor for the subject based on the current hand video includes: In the current hand video, determine the short window where the subject's hand is in a resting state or in a standard posture, and determine the palm width and fingertip span of the subject's hand, and determine the monocular depth for the current hand video; In the current hand video, residual tremor noise of the subject's hand in a resting state is determined; Based on the short window, palm width, fingertip span, monocular depth, and residual tremor noise, the current shooting influence factor for the current shooting of the subject is determined.

4. The adaptive hand tremor assessment method according to claim 3, characterized in that, The adaptive hand tremor assessment method also includes: Update the current shooting impact factor; The process of determining the true tremor amplitude of the subject's hand based on the current tremor intensity, the current imaging impact factor, and the initial imaging impact factor includes: Based on the current tremor intensity, the updated current shooting influence factor, and the initial shooting influence factor, the actual tremor amplitude of the subject's hand is determined, and the updated current shooting influence factor is used to determine the current shooting influence factor.

5. The adaptive hand tremor assessment method according to claim 1, characterized in that, The determination of the initial shooting influence factors for the initial shooting of the subject based on the initial hand video includes: The main features of the subject's hand are extracted from the initial hand video, wherein the initial hand video contains videos of the subject performing at least two standard postures; Based on the aforementioned key features, an initial shooting influence factor is generated for the initial shooting of the subject.

6. The adaptive hand tremor assessment method according to claim 5, characterized in that, The adaptive hand tremor assessment method also includes: If an alignment sample with a physical scale exists, then the initial shooting influence factor is calibrated according to the alignment sample; The process of determining the true tremor amplitude of the subject's hand based on the current tremor intensity, the current imaging impact factor, and the initial imaging impact factor includes: Based on the current tremor intensity, the current shooting influence factor, and the calibrated initial shooting influence factor, the current shooting influence factor after updating the actual tremor amplitude of the subject's hand is determined.

7. The adaptive hand tremor assessment method according to any one of claims 1-6, characterized in that, The adaptive hand tremor assessment method also includes: Generate a tremor assessment report for the subject, the tremor assessment report including at least one of the tremor frequency and tremor amplitude for the subject.

8. The adaptive hand tremor assessment method according to any one of claims 1-6, characterized in that, The process of determining the true tremor amplitude of the subject's hand based on the current tremor intensity, the current imaging impact factor, and the initial imaging impact factor includes: The product of the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor is taken as the true tremor amplitude of the subject's hand.

9. An evaluation device, characterized in that, The evaluation device includes: The first acquisition module is used to acquire the current hand video of the subject's hand, and based on the current hand video, determine the current tremor intensity of the subject's hand and the current shooting influence factor for the subject's current shooting. The current tremor intensity is the tremor intensity that is independent of the distance between the shooting device and the subject, and the current shooting influence factor represents the current conversion coefficient between the pixel points of the hand in the current hand video and the actual distance. The second acquisition module is used to acquire an initial hand video of the subject's hand at a preset time before the current time, and based on the initial hand video, determine an initial shooting influence factor for the initial shooting of the subject. The initial shooting influence factor represents the initial conversion coefficient between the hand pixels in the initial hand video and the actual distance. The determination module is used to determine the true tremor amplitude of the subject's hand based on the current tremor intensity, the current shooting influence factor, and the initial shooting influence factor, and to evaluate the true tremor amplitude.

10. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the adaptive hand tremor assessment method as described in any one of claims 1-8.

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