A Parkinson tremor intelligent control bracelet

Abstract

The utility model provides a kind of Parkinson tremor intelligent control bracelet, wristband is wound in user hand, built-in IMU sensor;Shell bottom surface is equipped with the opening that wristband passes through, outer edge is equipped with baffle;Control panel is positioned by baffle in the shell interior, is equipped with tremor monitoring module, medication reminding module and somatosensory game module;Tremor monitoring module built-in accelerometer;Medication reminding module is equipped with buzzer and red LED lamp;Somatosensory game module is enabled when medication reminding module is not triggered, external OLED screen;Power supply module includes lithium battery and charging module, lithium battery is powered for charging module, charging module is powered for control panel by Type-C interface;The utility model bracelet adopts wristband type design, structure is light and clever, supports quick disassembly and replacement, adapts different wrist circumference demand;Reserved sensor window and key anti-misoperation groove, ensure function stability;Built-in power module, battery endurance capacity is enough.

Description

Technical Field

[0001] This utility model relates to the field of medical technology, and in particular to a smart control bracelet for Parkinson's tremor. Background Technology

[0002] Currently, various fitness trackers have become increasingly popular in the market. Essentially, they are pedometers with built-in simple sensors, primarily used to monitor calorie consumption. However, people expect these wearable devices to have more functions, a crucial one being the ability to monitor the wearer's health, especially for more complex conditions such as blood sugar levels, stroke risk, and Parkinson's tremors, providing better early warning capabilities.

[0003] Currently, wearable health monitoring devices have emerged in domestic and international markets, including: non-invasive diabetes monitoring devices, Parkinson's syndrome monitoring devices, wearable devices for preventing sudden heart attacks and strokes, lifestyle monitors for the elderly, wearable hearing aids, and wearable vision enhancers.

[0004] Despite significant progress in the detection, diagnosis, and treatment of Parkinson's disease, smart wearable devices still face numerous challenges. For example, the battery life of the devices and their placement may affect the accuracy of research results. Clinical diagnosis and treatment heavily rely on dynamic tremor monitoring, but current technologies have significant limitations. Medical devices (such as PKG™ watches) are precise but bulky (≥120g), making them difficult to use in daily life. Summary of the Invention

[0005] The purpose of this invention is to provide a smart control bracelet for Parkinson's tremor, a smart wearable device designed for Parkinson's disease patients and high-risk groups.

[0006] To achieve the above objectives, the technical solution of this utility model is as follows: A smart bracelet for controlling Parkinson's tremor, characterized in that it includes: The wristband wraps around the user's hand and contains an IMU sensor to monitor Parkinson's tremors. The outer shell is rectangular and disc-shaped, with an opening on the bottom surface through which the wrist strap passes, and a baffle along the circumferential edge. The control panel, which is limited by a baffle and is located inside the housing, is equipped with a tremor monitoring module, a medication reminder module, and a motion-sensing game module. The tremor monitoring module has a built-in accelerometer, the medication reminder module has a buzzer and a red LED light, the motion-sensing game module is activated when the medication reminder module is not triggered, and the motion-sensing game module is connected to an external OLED screen. The power supply module includes a lithium battery and a charging module. The lithium battery powers the charging module, and the charging module powers the control board via a Type-C interface.

[0007] Furthermore, one side of the baffle is bent inward to provide an anti-accidental contact plate.

[0008] Furthermore, a power supply port is provided on the other side of the baffle, which accommodates a Type-C interface.

[0009] Furthermore, the baffle has inwardly bent blocks at both ends, and the control plate is interference-fitted with the blocks at both ends to be snapped into the interior of the housing.

[0010] Furthermore, it includes a display screen mounted on the control board, the display screen being connected to the control board.

[0011] Furthermore, the inner wall of the outer shell is provided with a silicone buffer layer.

[0012] This utility model wristband adopts a wristband design, which is lightweight and supports quick replacement to adapt to different wrist sizes; it has reserved sensor windows and button anti-accidental touch grooves to ensure stable function; and it has a built-in power supply module with sufficient battery life. This invention balances structural strength and wearing comfort, providing a significantly better user experience than traditional wristbands. Attached Figure Description

[0013] Figure 1 This is a schematic diagram of the structure of the bracelet shell of this utility model; Figure 2 This is a system schematic diagram of the power supply module of this utility model; Figure 3 This is a schematic diagram of the dual-thread design of this utility model; Figure 4 This is a schematic diagram of the monitoring thread process of this utility model; Figure 5 This is a schematic diagram of the intervention thread process of this utility model.

[0014] Figure label: 1. Outer shell, 2. Opening, 3. Baffle, 4. Anti-accidental contact plate, 5. Power supply port, 6. Stop block; 7 charging ports, 8 control board, 9 Type-C interface, 10 charging module, 11 lithium battery. Detailed Implementation

[0015] The technical solution of this utility model will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this utility model. Based on the embodiments of this utility model, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this utility model.

[0016] This utility model discloses a smart control bracelet for Parkinson's tremor, including a wristband, a shell 1, a control board 8, and a power supply module.

[0017] The wristband is wrapped around the user's hand. The appropriate width and length of the wristband are cut according to the size of the watchband's serial number and the wearer's wrist size. The wristband is then assembled and tested. A watchband buckle can be used, or Velcro can be used to directly connect the two ends of the watchband. One-handed operation is supported.

[0018] The wristband has a built-in IMU sensor for monitoring Parkinson's tremor. The IMU sensor uses an MPU6050 six-axis motion sensor to collect data on the user's hand movements. The wristband also has a built-in wired or wireless data transmission system for communicating with smart devices.

[0019] like Figure 1 As shown, the outer shell 1 is rectangular and disc-shaped. The outer shell 1 is made of PLA material and printed with 100% fill rate. The embedded silicone buffer layer reduces hardware vibration interference and improves data acquisition accuracy. The bottom surface of the outer shell 1 has two openings 2 for the wrist strap to pass through, and the outer edge has a baffle 3 along the circumference.

[0020] The bottom of the outer shell 1 is curved to fit the curvature of the wrist, and the outer shell 1 has a matte frosted surface to avoid glare.

[0021] like Figure 2 As shown, the power supply module includes a lithium battery 11 and a charging module 10. The lithium battery 11 supplies power to the charging module 10, and the charging module 10 supplies power to the control board 8 through the Type-C interface 9. The components of the power supply module are connected together by welding.

[0022] like Figure 1 As shown, the side of the baffle 3 closest to the human body is bent inward to provide an anti-accidental touch plate 4 to prevent the user from accidentally touching the touch button. The side of the baffle 3 away from the human body is provided with a power supply port 5, which accommodates a Type-C interface 9. The front and rear ends of the baffle 3 are bent inward to provide a stop block 6. The two ends of the control board 8 are interference-fitted with the stop block 6 to be inserted into the housing 1. The front end of the baffle 3 is provided with a charging port 7, which is used to connect an external charging cable to the charging module 10.

[0023] The control board 8 is limited and positioned inside the housing 1 by the baffle 3. The control board 8 adopts ESP32 and is equipped with a tremor monitoring module, a medication reminder module and a motion-sensing game module.

[0024] When in use, relevant settings can be made on the IoT platform cloud via a smart terminal. The smart terminal obtains the tremor sign data monitored by the wristband, and the data is stored on the IoT platform cloud. Doctors and family members can view the monitoring and usage data by accessing the IoT platform cloud webpage or mini-program. They can also send commands to the wristband via the IoT platform cloud to modify program parameters in order to adjust the medication plan.

[0025] The tremor monitoring module acquires the user's hand movements through an IMU sensor and a built-in accelerometer, and monitors the user's tremor vital signs data, including the frequency and duration of the tremor. The control board 8 is also connected to a display screen, which is used to display the frequency and duration of the tremor, and has buttons A, B and O.

[0026] The tremor monitoring module acquires 50Hz high-frequency data through timer interrupts. After the acceleration data is filtered by sliding window mean, the energy characteristics of the 4-9Hz tremor frequency band are extracted using Fast Fourier Transform (FFT) and then uploaded to the cloud in encrypted form via MQTT protocol.

[0027] The IoT platform uses the KNN algorithm to achieve intelligent tremor classification in the cloud. The model is trained based on a historical patient tremor energy feature dataset (n=1000) (k=5 nearest neighbors). The similarity of input features is calculated using Manhattan distance, and the output is tremor state (True / False) and confidence level (0-1). The model supports incremental learning, and the decision boundary can be dynamically updated with new user data. The classification accuracy reaches 86.4% (95% CI: 83.1%-89.7%). The classification result is returned to the tremor monitoring module within 200ms, triggering local alarms or synchronizing to the doctor's platform, forming a real-time closed loop of "perception-analysis-intervention".

[0028] The medication reminder module achieves precise management through timed polling and hardware interrupts. The medication time is hard-coded in control board 8. When the predetermined time is reached, a buzzer (100dB) and a red LED warning are triggered, which continues until the user presses a button to confirm. After the user confirms or no action is taken after the timeout, the medication status is encrypted and uploaded to the cloud for HMM model analysis of missed dose patterns. The medication reminder module can remind users to take their medication at regular intervals and provide medication information, including the name of the drug, dosage, and method of use.

[0029] The IoT platform uses a Hidden Markov Model (HMM) in the cloud to analyze the temporal patterns of medication behavior. It transforms medication records (encoded as 0 / 1 sequences by time period) into a state transition probability matrix and predicts future states based on the three most recent medication records. If a high-risk pattern is hit, such as consecutive missed doses, a real-time alert is pushed to the family member. The cloud model is automatically retrained every 24 hours to adapt to changes in patient behavior.

[0030] The motion-sensing game module is activated when the medication reminder module is not triggered. It connects to an external OLED screen and provides games through acceleration mapping and real-time rendering. The motion-sensing game module can randomly select one game from shooting games and pinball games.

[0031] In the target shooting game, acceleration data is smoothed by Kalman filtering and converted into cursor coordinates on the OLED screen (dynamic target shooting). After hitting the target, a new target point is generated, and the score is encrypted and uploaded to the cloud. The motion-sensing game module uses integer operations and pixel-level refresh to ensure a smooth 10fps frame rate.

[0032] The IoT platform cloud can achieve adaptive game difficulty through deep Q network (DQN). Specifically, it takes the user's historical performance (average score, number of tremor interferences, average time) as input, outputs game parameter adjustment instructions, and retrains the model every 6 hours to dynamically balance challenge and feasibility. The new parameters take effect immediately after the device receives them, without the need for a restart, ensuring training continuity.

[0033] The control method of this utility model for the Parkinson's tremor smart control bracelet is used to control the Parkinson's tremor smart control bracelet. The control method includes a synchronous monitoring thread and an intervention thread. See [link to relevant documentation]. Figure 3 ; The monitoring thread includes the following steps: Step S101) The IMU sensor, in conjunction with the accelerometer, collects acceleration data of the user's hand movements in real time; Step S102) The acceleration data is filtered by sliding window mean; Step S103) Extract energy features of the 4-9Hz flutter frequency band using Fast Fourier Transform; Step S104) The energy characteristics are encrypted using the MQTT protocol and uploaded to the cloud for processing; Step S105) The cloud uses the KNN algorithm to achieve intelligent tremor classification, and the classification results are fed back to the tremor monitoring module; The intervention thread includes the following steps: Step S201) Medication reminder module and cloud synchronization of medication plan; Step S202) The medication reminder module obtains the current time. When the scheduled medication time is reached, it triggers a buzzer and a red LED light to warn the user. The warning continues until the user presses the button to confirm. Step S203) Activate the motion-sensing game module during non-pre-medication time, randomly provide a shooting game or a pinball game, and convert the acceleration data into cursor coordinates on the OLED screen after being smoothed by Kalman filtering. Step S204) The game score is encrypted and uploaded to the cloud.

[0034] In one embodiment, such as Figure 4 As shown, the monitoring thread steps are as follows: Step 1) Initialize the IMU sensor and tremor monitoring module, then proceed to Step 2; Step 2) Determine if the user's hand is shaking in this second. If yes, proceed to step 3; otherwise, proceed to step 1. Step 3) Calculate the number of shakes in one second and determine if the number is ≥4. If yes, skip to step 4; otherwise, skip to step 1. Step 4) Calculate the number of shakes in the next second and determine if the number is ≥4. If yes, proceed to step 5; otherwise, proceed to step 6. Step 5) Accumulate the number of shakes and duration, then skip to step 4; Step 6) Send the total number of shakes and total duration data to the IoT platform, then proceed to Step 1.

[0035] In one embodiment, such as Figure 5 As shown, the steps for intervening in the thread are as follows: Step 1) Initialize the medication reminder module, then proceed to Step 2; Step 2) Determine if it is time to take the medication. If yes, proceed to step 3; otherwise, proceed to step 6. Step 3) Remind the user to take the medication, then proceed to step 4; Step 4) Determine if the user has pressed button B. If yes, proceed to step 5; otherwise, proceed to step 6. Step 5) Send medication records to the IoT platform, then proceed to step 6; Step 6) Determine if the user has pressed button A. If yes, proceed to step 7; otherwise, proceed to step 9. Step 7) Generate a random number (0 or 1). If the random number is 1, provide a pinball game; if the random number is 0, provide a dynamic shooting game. Skip to step 8. Step 8) Determine if the user has pressed button O. If yes, stop the game and proceed to step 9. If no, continue the current game. Step 9) Display the clock and monitoring data, then jump to step 1.

[0036] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this utility model, and are not intended to limit it. Although the utility model has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this utility model.

Claims

1. A smart bracelet for controlling Parkinson's tremor, characterized in that, include The wristband wraps around the user's hand and contains an IMU sensor to monitor Parkinson's tremors. The outer shell is rectangular and disc-shaped, with an opening on the bottom surface through which the wrist strap passes, and a baffle along the circumferential edge. The control panel, which is limited by a baffle and is located inside the housing, is equipped with a tremor monitoring module, a medication reminder module, and a motion-sensing game module. The tremor monitoring module has a built-in accelerometer, the medication reminder module has a buzzer and a red LED light, the motion-sensing game module is activated when the medication reminder module is not triggered, and the motion-sensing game module is connected to an external OLED screen. The power supply module includes a lithium battery and a charging module. The lithium battery powers the charging module, and the charging module powers the control board via a Type-C interface.

2. The Parkinson's tremor smart control bracelet according to claim 1, characterized in that, One side of the baffle is bent inward to provide an anti-accidental contact plate.

3. The Parkinson's tremor smart control bracelet according to claim 2, characterized in that, The other side of the baffle is provided with a power supply port, which accommodates a Type-C interface.

4. The Parkinson's tremor smart control bracelet according to claim 2, characterized in that, The baffle has inwardly bent blocks at both ends, and the control plate is interference-fitted with the blocks at both ends to be snapped into the interior of the housing.

5. The Parkinson's tremor smart control bracelet according to claim 4, characterized in that, It includes a display screen mounted on the control board, and the display screen is connected to the control board.

6. The Parkinson's tremor smart control bracelet according to claim 1, characterized in that, The inner wall of the outer casing is provided with a silicone cushioning layer.

Images