The aim of this project is to improve the clinical acceptance of a multifingered Prosthetic Hand through sensor fusion techniques. The system measures the electrical activity of the forearm muscles and also detects the shape of object to be grasped. A microprocessor based system then decides the bes
Prosthetic Grasping of Objects using Integrated sEMG and Vision
The aim of this project is to improve the clinical acceptance of a multifingered Prosthetic Hand through sensor fusion techniques. The system measures the electrical activity of the forearm muscles and also detects the shape of object to be grasped. A microprocessor based system then decides the best possible hand gesture to grasp the object.
sEMG signals are detected and amplified by indigenously developed electrodes. sEMG signals are processed to recognize hand gestures. Actuators such as motors are then controlled for individual finger movements resulting in desired gestures.
sEMG Signal Processing
•Basic Grasp Detection using sEMG Signals
•Image Acquisition
•Object Shape Detection
•Object Orientation/Axis Detection
•Prosthetic Hand Grasp formation
Electrical activity of muscles will be measured by sEMG electrodes.
•Micro Processor will receive these signals.
•Based on these signals a Micro Processor will decide the grasp that Amputee wants to make (Cylindrical, Lateral or Pinch etc).
•Vision system consist a Camera attached to a Single Board Computer.
•Vision system will assist the EMG system by:
–Detecting an object.
–Finding its axis.
•If the object is present then Single Board Computer will align the Amputee’s hand to grasp that object.
•IMU’s (Inertial Measurement Unit) are used to detect the position of hand.
Rehabilitation Technology
Rehabilitation technology is a profession that uses technology to help people with physical disabilities increase their independence.
•Prosthesis Control
Prosthesis control is a method for controlling a prosthesis in such a way that the controlled robotic prosthesis restores a biologically accurate gait to a person with a loss of limb.
•Wearable Systems
A smart wearable system (SWS) is an end-to-end integrated and connected system that has the following features: one or more sensors and actuators etc.
Micro Controller Arm Cortex STM32F103C8T6
STM32F103C8T6 is widely used in industries and medical fields where high processing is required.In this project it is used to control individual fingers of hand.
DRV 8830
DRV 8830 is a motor driver and I2C compatible interface.
RaspberryPi 3 B+
It is Linux based Single Board computer which is used for Vision. A Camera will be connected to this to recognize objects.
Camera A4TECH Pk-720G
The objective of Camera is to detect the Object which Amputee wants to grasp.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Arm Cortex M3 | Equipment | 2 | 400 | 800 |
| Debugger | Equipment | 2 | 300 | 600 |
| Raspberry Pi 3 B+ with Case | Equipment | 2 | 8000 | 16000 |
| 3d Printing of Hand Parts | Equipment | 12 | 500 | 6000 |
| Pulleys of Mini Motors | Equipment | 12 | 165 | 1980 |
| Socket Adapter | Equipment | 1 | 1500 | 1500 |
| Mini Motors | Equipment | 5 | 1000 | 5000 |
| Cells | Equipment | 4 | 250 | 1000 |
| Motor Couplers | Miscellaneous | 3 | 50 | 150 |
| Nuts & Bolts | Equipment | 12 | 20 | 240 |
| HDMI Converter | Equipment | 1 | 500 | 500 |
| VGA Cable | Equipment | 1 | 214 | 214 |
| Memory Card | Equipment | 2 | 700 | 1400 |
| Motor Drivers | Equipment | 8 | 200 | 1600 |
| SMD Resistors | Equipment | 10 | 80 | 800 |
| Camera | Equipment | 1 | 1000 | 1000 |
| Total in (Rs) | 38784 |
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