WO2016117998A1

WO2016117998A1 - A robot-assisted therapy system

Info

Publication number: WO2016117998A1
Application number: PCT/MY2015/050158
Authority: WO
Inventors: Che Fai YEONG; Eileen Lee Ming SU; Kang Xiang KHOR; Patrick Jun Hua CHIN
Original assignee: Universiti Teknologi Malaysia (UTM)
Current assignee: Universiti Teknologi Malaysia (UTM)
Priority date: 2015-01-20
Filing date: 2015-12-31
Publication date: 2016-07-28
Anticipated expiration: 2017-07-20

Abstract

The present invention relates to a robot-assisted therapy system (1000) for 5 treating an impaired wrist of a stroke patient. The robot-assisted therapy system (1000) comprises of a pulse oximeter (100); a computing device (200) having a processor (210); and a robotic device (300) having a housing (350), a power switch (370), and an emergency switch (380). The robotic device (300) further comprises of a controller (330); a motor (340); a handle (360); a current sensor (310); and a rotary 10 encoder (320). Additionally, the current sensor (310), the rotary encoder (320), the controller (330), and the motor (340) are enclosed within the housing (350).

Description

A ROBOT-ASSISTED THERAPY SYSTEM

FIELD OF INVENTION

The present invention relates to a robot-assisted therapy system to train movements of a stroke patient.

BACKGROUND OF THE INVENTION

The development of rehabilitation robots has become recovery training aids to stroke patients. With the aid of robotic devices, different modules of rehabilitation trainings are developed to stimulate different sensorimotor functions. Rehabilitation robots are well tolerated by patients, and are found effective to aid stroke patients who are suffering paralysis, and at the same time enhancing efficiency of therapy.

An example of such robotic device is provided by US Patent No. 61 17093 which discloses a device for hand and wrist rehabilitation using a magnetorheological fluid controllable resistance brake. The magnetorheological fluid is controlled to provide different level of resistance. This is done by manipulating the magnetic field intensity through the control circuit to adjust the viscosity of the magnetorheological fluid in the brake system. This enables the patient to determine their training according to their recovery rate by adjusting the controller to a level of resistance suitable with their recovery rate. The device also uses tool elements that are focusing on the wrist movement to daily usage in life.

However, the device does not trigger the patient's sense of touch. The resistance brake system is only able to stimulate muscle strength, but does not stimulate a realistic touch sensation for the patients. Hence, there is a need to provide a rehabilitation robot that addresses the drawback of the prior art.

SUMMARY OF INVENTION

The present invention relates to a robot-assisted therapy system (1000). The robot-assisted therapy system (1000) comprises of a pulse oximeter (100) to measure the heartbeat of a patient; a computing device (200) having a processor (210) to process algorithms and operations; and a robotic device (300) having a housing (350), a power switch (370) to switch on and off the robotic device (300), and an emergency switch (380) to switch off the robotic device if the patient experiences any difficulty. The robotic device (300) further comprises of a controller (330) connected to the processor (210) to control and drive a motor (340); the motor (340) connected to the controller (330) to generate haptic effects; a handle (360) to fit the needs of different training modes to emulate daily activities; a current sensor (310) connected to the controller (330) to measure the current level and to estimate torque generated by the motor (340); and a rotary encoder (320) connected to the controller (330) to detect if the handle (360) has moved from its initial position. Additionally, the current sensor (310), the rotary encoder (320), the controller (330), and the motor (340) are enclosed within the housing (350).

Preferably, the handle (360) is detachable from the robotic device (300).

Preferably, the detachable handle (360) includes a forearm handle (360a), a wrist handle (360b), a circular handle (360c), a key handle (360d) and a long handle (360e).

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

FIG. 1 illustrates a block diagram of a robot-assisted therapy system (1000) according to an embodiment of the present invention. FIGS. 2 (a - d) illustrate control algorithm diagrams for a motor (340) in a robotic device (300) of the robot-assisted therapy system (1000).

FIG. 3 illustrates a detail drawing of the robotic device (300) of the robot-assisted therapy system (1000) of FIG. 1 .

FIG. 4 illustrates different types of handles (360) of the robotic device (300).

FIG. 5 illustrates a flowchart of a method for operating the robot-assisted therapy system (1000) of FIG. 1. DESCRIPTION OF THE PREFFERED EMBODIMENT

A preferred embodiment of the present invention will be described herein below with reference to the accompanying drawings. In the following description, well known functions or constructions are not described in detail since they would obscure the description with unnecessary detail.

FIG. 1 illustrates a robot-assisted therapy system (1000) according to an embodiment of the present invention. The usage of the robot-assisted therapy system (1000) may include but is not limited to treating an impaired wrist of a patient having a stroke. The robot-assisted therapy system (1000) operates in three training modes which include a passive mode, an assistive mode and an active mode. The passive mode is used for helping the patient who cannot move his/her wrist, the assistive mode is used for helping the patient who can move the wrist but only in a restricted range of movement, while the active mode is used for helping the patient to improve muscle function by increasing resistance according to the patient's recovery rate. For each type of training mode, the range of movement, strength, level, duration of time and number of repetition can be set in a graphical user interface before the training begins. In addition to the training modes, the robot-assisted therapy system (1000) is able to generate haptic feedback during the training for the patient to experience virtual object.

The robot-assisted therapy system (1000) comprises of a pulse oximeter (100), a computing device (200), and a robotic device (300). The pulse oximeter (100) which is connected to the computing device (200) is configured to measure the heartbeat of the patient. The measured heartbeat is sent to the computing device (200) to compare with a predetermined threshold level. By measuring the heartbeat, the stress level of the patient undergoing the training can be determined. If the measured heartbeat is higher than the predetermined threshold level, this indicates that the stress level of the patient is high and thus, a warning message is indicated by the computing device (200) to advise the patient to take a rest rather than to proceed with the training.

The computing device (200) includes a processor (210) which is connected to a monitor (220) and a speaker (230). Moreover, the processor (210) is connected to a controller (330) in the robotic device (300). The processor (210) is configured to process algorithms and operations, including sound, visual and haptic sensation. The monitor (220) is configured to display the graphical user interface of a virtual environment. The speaker (230) is configured to provide audio feedback to generate more realistic virtual environment to motivate the patient to do more exercise during the training.

The robotic device (300) includes a current sensor (310), a rotary encoder (320), a controller (330), and a motor (340). The current sensor (310), which is connected to the controller (330), is configured to measure the current level and to estimate the torque generated by the motor (340) during the training. The rotary encoder (320), which is also connected to the controller (330), is configured to detect if a handle (360) of the robotic device (300) as shown in FIG. 3 is at its initial position or not. Besides the current sensor (310) and the rotary encoder (320), the controller (330) is also connected to the processor (210) of the computing device (200). The controller (330) is configured to control and drive the motor (340). In particular, the controller (330) sends a torque signal to the motor (340) to rotate the motor (340), wherein the motor (340) generates haptic effects when the handle (360) is being operated by the patient. Reference now is made to FIGS. 2 (a-d) which illustrate control algorithm diagrams for the motor (340). To provide haptic effect by the motor (340), a control algorithm is implemented. The motor (340) implements three different models, which are weight control, wall control and magnet control as shown in FIG. 2 (a). The pulse width modulation motor command (MotorPWM) is defined as:

MotorPWM = Weight Control + Wall Control + Magnet Control

The first model, which is the weight control, generates haptic effect for the patient to experience virtual weight, wherein the weight control is defined as:

Weight Control = K_w x Weight x Lever x sin(0)

From the equation, K_w refers to a weight control gain which determines the amount of weight control that affects the output. The Weight refers to the virtual weight which is attached to a virtual haptic knob. The Lever refers to length of the lever which is connected to the virtual haptic knob. The angle Θ refers to the angle rotation of the virtual haptic knob. The relationship of the weight control equation is shown in FIG. 2 (b).

The second model, which is the wall control, generates haptic effect for the patient to experience virtual collisions, wherein the wall control equation is defined as: with collision

no collision

From the equation, p refers to the wall control proportional gain. e(t) refers to the error on the wall collision, which is derived from the error between the tip of the lever and the wall position. K_D refers to the wall control derivative gain. Both constants _Pand oare tuned by using trial and error method.

The third model, which is the magnet control, generates haptic effect for the patient to experience a virtual gravitational feedback. The magnet control applies Newton's universal law of gravity, based on the equation below:

M_tM₂

Length²

wherein

Length =

From the equation, G refers to the gravitational constant and M refers to the mass of an object. The Length refers to the distance between two objects. The equation is simplified by assuming Mi and M? to be one, resulting the equation of F_M to be as follows:

The resulting equation of F_M represents attraction between two objects. To represent the implementation of the magnetic attraction and repulsion, the magnet control is defined as:

Magnet Control = F x Lever

wherein

F = F_M x cos β = a - 90°

From the equations, F represents the relationship between F_M and angle β between F_M and F. Angle a represents the angle between the Length and the Lever. The relationship between the Length, Lever, β, a, and magnet control is as shown in FIGS. 2 (c - d).

Referring now to FIG. 3, it illustrates a detail drawing of the robotic device (300) of the robot-assisted therapy system (1000). Besides the current sensor (310), the rotary encoder (320), the controller (330), and the motor (340) which are embedded inside the robotic device (300), the robotic device (300) further comprises of a housing (350), a handle (360), a power switch (370), and an emergency switch (380). The housing (350) is used to enclose the motor (340), the rotary encoder (320), the current sensor (310), and the controller (330). The handle (360), which is preferably a detachable handle, is attached to the robotic device (300) at point A. The handle (360) fits the needs of different training modes to emulate daily activities. The power switch (370) is used to switch on and off the robotic device (300), whereas the emergency switch (380) is used to switch off the robotic device (300) if the patient experiences any difficulties during the rehabilitation training. Referring now to FIG. 4, it shows different types of handles (360) of the robotic device (300). The handles (360) are attachable to the robotic device (300) at point A as shown in FIG. 3. The different types of handles (360) allow the patient to emulate daily activities such as using a key, opening a door, or grabbing a can. The first handle type is a forearm handle (360a) to train the forearm of the patient. By holding the forearm handle (360a), the patient trains the forearm by rotating the handle. The second handle type is a wrist handle (360b) which is used to train wrist movement by gripping and moving the wrist handle (360b). The third handle type is a circular handle (360c) which is similar to a door knob which is used to train the patient to turn the door knob. The fourth handle type is a key handle (360d) which is used to train the patient to turn a key slotted by holding the key handle (360d). The fifth handle type is a long handle (360e) which is used to train the patient to grab and turn the long handle (360e) using his/her wrist. Reference is now made to FIG. 5 which shows a flowchart of a method for operating the robot-assisted therapy system (1000). Initially, strength and a range of movement of the patient are inputted in the user interface before the training starts as in step 501. Thereon, the training mode of the robotic device (300) is selected as in step 502, wherein the training mode can either be a passive mode, an assistive mode, or an active mode. For each training mode, the training session is continuous preferably for one minute.

If the passive mode is selected, the robotic device (300) moves the hand of the patient automatically based on the range of movement that has been set. The range of movement is set to a certain degree while a number of repetitions is inputted in the graphical user interface as in step 510. Thereon, the processor (210) sends a signal to the controller (330) for the motor (340) to generate torque to rotate the motor (340). As the motor (340) rotates, the handle (360) also rotates as in step 511. The robotic device (300) moves the hand of the patient automatically based on the range of movement that has been set. If there is still remaining number of repetitions left as in decision 512, the motor (340) rotates the handle (360) as in step 511. However, if there is no more remaining number of repetitions, the training session ends. If the assistive mode is selected, the patient moves the handle (360) of the robotic device (300) within a duration of time based on the range of movement that has been set. The range of movement, the number of repetition and the time duration are inputted in the graphical user interface as in step 520. The motor (340) is in a standby mode as the patient moves the handle (360) within the duration of time as in step 521. The rotary encoder (320) then detects the position of the handle (360) that is moved by the patient, whereas the current sensor (310) senses and measures the current of the torque generated by the motor (340). If the patient is able to move the handle (360) within the duration of time as in decision 522, the motor (340) remains in standby mode until the end of the training session as in step 521 . However, if the patient does not move the handle within the duration of time as in decision 522, the controller (330) sends a signal to the motor (340) to rotate the handle. The motor (340) then rotates the handle (360) to assist the patient to complete the training session as in step 523. If the training session is not completed as in decision 524, the motor (340) continues to assist the patient until the training is completed. However, if the training session is completed as in decision 524, the training session ends.

If the active mode is selected, the patient moves the handle (360) of the robotic device (300) based on the range of movement that has been set, strength, level, duration of time and number of repetition which are inputted as in step 530. The motor (340) is in standby mode as in step 531 as the patient moves the handle (360). If the position of the handle (360) is detected to be at its initial position by the rotary encoder (320) as in decision 532, the motor (340) continues to be in standby mode until the training session ends. However, if the position of the handle (360) is not at the initial position, the controller (330) sends a signal to the motor (340) to move the handle (360) to an opposite direction of the range of movement that was inputted as in step 533. Thereon, the patient has to move the handle (360) back to the initial position. If the position of the handle is not back to the initial position as in decision 534, the controller (330) signals the motor (340) to move the handle (360) to an opposite direction until the position of the handle is back to the initial position. However, if the position of the handle (360) is back to the initial position as in decision 534, the motor (340) continues to be in standby mode until the training session ends.

While embodiments of the invention have been illustrated and described, it is not intended that these embodiments illustrate and describe all possible forms of the invention. Rather, the words used in the specifications are words of description rather than limitation and various changes may be made without departing from the scope of the invention.

Claims

A robot-assisted therapy system (1000) comprising:

a) a pulse oximeter (100) to measure the heartbeat of a patient;

b) a computing device (200) having a processor (210) to process algorithms and operations; and

c) a robotic device (300) having a housing (350), a power switch (370) to switch on and off the robotic device (300), and an emergency switch (380) to switch off the robotic device if the patient experiences any difficulty,

characterised in that the robotic device (300) further comprising:

i. a controller (330) connected to the processor (210) to control and drive a motor (340);

ii. the motor (340) connected to the controller (330) to generate haptic effects;

iii. a handle (360) to fit the needs of different training modes to emulate daily activities;

iv. a current sensor (310) connected to the controller (330) to measure the current level and to estimate torque generated by the motor (340); and

v. a rotary encoder (320) connected to the controller (330) to detect if the handle (360) has moved from its initial position, wherein the current sensor (310), the rotary encoder (320), the controller (330), and the motor (340) are enclosed within the housing (350).

The robot-assisted therapy system (1000) as claimed in claim 1 , wherein the handle (360) is detachable from the robotic device (300).

The robot-assisted therapy system (1000) as claimed in claim 2, wherein the detachable handle (360) includes a forearm handle (360a), a wrist handle (360b), a circular handle (360c), a key handle (360d) and a long handle (360e).