US 12,269,161 B2 · Multi-degree-of-freedom myoelectric artificial hand control system and method for using same

Abstract

Provided are a multi-degree-of-freedom myoelectric artificial hand control system and a method for using same. The system comprises a robotic hand, a robotic wrist (2), a stump receiving cavity (1) and a data processor (3), wherein the robotic hand and the stump receiving cavity (1) are respectively mounted on two ends of the robotic wrist (2); a multi-channel myoelectric array electrode oversleeve, a control unit circuit board, and a battery are connected in the stump receiving cavity (1); and the other end of the control unit circuit board is connected to the robotic hand and the robotic wrist (2). The method for using the system comprises the following steps: (S1) a user wearing a multi-channel myoelectric array electrode oversleeve, and connecting a battery and a control unit circuit board; (S2) the user completing a gesture, collecting a surface electromyography signal and then uploading same to a data processor (3); (S3) the data processor (3) receiving the surface electromyography signal and inputting same into a neural network algorithm to generate a gesture prediction model; and (S4) the user controlling the multi-degree-of-freedom movement of the robotic wrist (2) and the robotic hand. By means of the system, continuous gestures and the gesture strength thereof can be identified, and multi-degree-of-freedom gestures can be made.

Claims7

Dependent claims

A multi-degree-of-freedom myoelectric artificial hand control system, comprising:

a robotic hand, a robotic wrist, a stump receiving cavity, and a data processor, wherein the robotic hand and the stump receiving cavity are respectively mounted on two ends of the robotic wrist, a multi-channel myoelectric array electrode oversleeve is connected in the stump receiving cavity, and a control unit circuit board and a battery are connected to the multi-channel myoelectric array electrode oversleeve;
the other end of the control unit circuit board is connected to the robotic hand and the robotic wrist;
the data processor sends a surface electromyography signal collection instruction to the control unit circuit board so that the multi-channel myoelectric array electrode oversleeve collects the surface electromyography signal, and further receives data and processes the data, to generate a gesture prediction model,
wherein the robotic wrist comprises a bevel gear set mechanism, a belt pulley drive mechanism, a servo motor, and a wrist support frame;
the bevel gear set mechanism is formed by four mutually engaged bevel gears arranged in a cross;
two of the bevel gears positioned on a horizontal direction are mounted on the wrist support frame and separately connected to a transmission wheel;
and the belt pulley drive mechanism is connected on the transmission wheel and is connected to the servo motor.

4 more elements

A method of using a multi-degree-of-freedom myoelectric artificial hand control system comprising:

a robotic hand, a robotic wrist, a stump receiving cavity, and a data processor, wherein the robotic hand and the stump receiving cavity are respectively mounted on two ends of the robotic wrist, a multi-channel myoelectric array electrode oversleeve is connected in the stump receiving cavity, and a control unit circuit board and a battery are connected to the multi-channel myoelectric array electrode oversleeve;
the other end of the control unit circuit board is connected to the robotic hand and the robotic wrist;
the data processor sends a surface electromyography signal collection instruction to the control unit circuit board so that the multi-channel myoelectric array electrode oversleeve collects the surface electromyography signal, and further receives data and processes the data, to generate a gesture prediction model, the method comprising the following steps:
(S1) a user wearing the multi-channel myoelectric array electrode oversleeve, and then connecting the control unit circuit board and the battery;
(S2) the user completing gestures according to an experimental movement sequence;
the data processor sending a surface electromyography signal collection instruction to the control unit circuit board;
and the control unit circuit board controlling the multi-channel myoelectric array electrode oversleeve to collect the surface electromyography signal and then store the signal in the control unit circuit board, and uploading it to the data processor;
(S3) the data processor receiving the surface electromyography signal and inputting the signal into a neural network algorithm, to generate a gesture prediction model;
and
(S4) the user wearing the stump receiving cavity, connecting the robotic hand and the robotic wrist, and identifying gestures in real time by using the generated gesture prediction model;
and the control unit circuit board controlling the multi-degree-of-freedom movement of the wrist and the robotic hand.

8 more elements

Dependencies are inferred from the claim text.

Multi-degree-of-freedom myoelectric artificial hand control system and method for using same

Life of this patent

Multi-degree-of-freedom myoelectric artificial hand control system and method for using same

Life of this patent

Abstract

Claims7