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This document describes a brain-controlled artificial leg system. There are four main types of brain waves - beta, alpha, theta, and delta - that are measured by an electrode cap placed on the skull. The brain waves are amplified, converted to digital signals, and processed to identify patterns. The signals are then sent to a microcontroller to control the movements of an artificial leg, such as walking and running. The brain-controlled artificial leg system is easier and cheaper to construct than normal artificial legs, and gives users full control over the artificial leg.
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SSB (1).pptx
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Microcontroller Based Obstacle Detection Device Using Voice Signal for the V...
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V01 i010403
Handicapped Assistance Device for Controlling Electrical Appliances Jamuna R - Assistant Professor,
Abhinai S - UG scholar,
Jhananadhan SP - UG scholar,
Department of ECE,
SNS College of Engineering, Coimbatore, India
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4 Way traffic controll new
This document summarizes a student project report on developing a microcontroller-based traffic light controller. It describes using an AT89C51 microcontroller programmed to control LED traffic lights through four phases to regulate traffic flow at an intersection. The circuit diagram and hardware components are explained, including a power supply, microcontroller, LEDs, 7-segment display, and common cathode configuration. Software and timing of the four light phases are also outlined to coordinate traffic flow from four directions through the intersection.
Clap Pattern Based Electrical Appliance control
1. The document describes a system to control electrical appliances like lights, fans, and TVs using hand claps.
2. The system uses a PIC microcontroller and condenser microphone to detect clap sounds and trigger relays connected to appliances.
3. Different clap patterns correspond to turning appliances on and off - one clap turns on the first device, two claps the second, and three claps the third. This provides a low-cost control method that could benefit physically challenged users.
BRAIN WAVE TECHNOLOGY - controlling electronic devices using brainwaves
With the growing dependence of mankind on the use of different electronic devices in day to day life, we want to have easy handling to these electronic devices and easiest one is the possible brain wave command to electronic devices without even to use of hands. Great advances have been achieved towards brain-computer interface (BCI) or controlling electronic devices with brain waves. Forget about keyboard, mouse, touch screens or even voice recognition: the real dream is thinking about what we want our electronic gadget to do. Imagine a future where we can move anything with just our mind. The idea of interfacing minds with machines has long captured the human imagination. Brainwaves are tiny electrical impulses released when a neuron fires in the brain. Brain-computer interface (BCI) technology works by monitoring these electrical impulses with a forehead sensor. The neural signals are input into our Think Gear chip, and interpreted with our patented Attention and Meditation algorithms. The measured electrical signals and calculated interpretations are then output as digital messages to the computer, toy, or mobile device, allowing you to see your brainwaves on the screen, or use your brainwaves to affect the device’s behavior. The four main types of brainwave patterns are delta, theta, alpha, and beta, and these can be detected and interpreted and signals sent wirelessly to devices to control them. The interface enables a direct communications pathway between the brain and the object to be controlled. BCIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions. BCI (brain–computer interface) has long been a favorite of sci-fi movies. A few paralyzed patients could soon be using a wireless brain-computer interface able to stream their thought commands as quickly as a home Internet connection
Monitoring and Controlling of BLDC motor using IOT
Brushless Direct Current motors are synchronous motors which operates on DC current. These motors have various advantages over Brushed DC motors such as low cost, high speed torque characteristics, noise less operation. Speed controlling is Very important. Speed of the motor is controlled by (ESC) electronic speed controlled. The parameters like Speed, Current, Power, Temperature and Voltage are Monitored on from remote access through the configured electronic gadgets by using the Internet Of things. the purpose of this project is to control and monitor the of Brushless DC (BLDC) motor by using IOT. The Internet of Things (IOT) has led to huge development in digital world. IOT is interface that helps communication between objects Brushless DC Motor (BLDCM) has various features like high efficiency, reliability, high weight to torque ratio. Hence these motors have major significances in the industries. By utilizing this IOT, controlling and monitoring of a system is done to obtain desired output.
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speed control of three phase induction motor using IOT
This project controls and monitors the speed of a three-phase induction motor using an Arduino and Node MCU controller. The Arduino implements PWM to control the motor speed using a three-phase driver circuit. Node MCU is used to increase and decrease the speed and establishes feedback of the speed to the Node MCU, which transmits the signal over Wi-Fi. This allows remote control of the motor speed through an IP address. The hardware components include a power supply, transformer, rectifier, inverter, driver circuit, Node MCU, Arduino and connecting wires. MATLAB is used to simulate the three-phase inverter and hardware results are obtained.
Gsm based smart card information for lost atm cards
This document describes a project to design a system that automatically detects lost ATM cards and sends an alert message to a predefined phone number. The system uses a GSM modem connected to a PIC microcontroller. The microcontroller is connected to an LCD display, smart card reader, and other components. When a lost card is inserted, the microcontroller will send an SMS message via the GSM modem. The document provides details on the various hardware components used and how they interface with each other.
IRJET- Smart Blind Stick for Visually Impaired People
This document describes a smart blind stick that uses various sensors to help visually impaired people navigate safely. The stick contains an ATmega8 microcontroller, ultrasonic sensors to detect obstacles, a moisture sensor to detect water, and a PIR sensor to detect humans. When obstacles are near, the microcontroller sends a signal to a Bluetooth module connected to a smartphone via an Android app. This allows the system to provide navigation assistance and help avoid dangers using sensors. The goal is to enable the visually impaired to move with greater ease, confidence and independence than with a traditional white cane.
Smart door project ppt shivnaresh likhar
This document presents a smart door system that uses a passive infrared (PIR) sensor to automatically open and close doors based on detecting nearby movement. The system includes an ATmega328 microcontroller, PIR sensor, relay driver IC, voltage regulator, LCD display, and other components. When the PIR sensor detects a person within its range, it sends a signal to the microcontroller to open the door. The door then automatically closes after a set time delay if no further movement is detected. The smart door system aims to provide convenience for disabled individuals and reduce contact with doors in places like hospitals.
Short Range Radar System using Arduino Uno
This document describes the design and implementation of a short range radar system using an Arduino Uno. The system uses an ultrasonic sensor mounted on a servo motor to detect objects within 180 degrees and up to 250cm. The Arduino transmits pulse signals to the ultrasonic sensor and calculates distance based on the echo return time. Distances are sent to MATLAB via UART communication and displayed graphically. The system is able to continuously monitor and detect obstacles in a short range area.
Automatic mall elevator
This document describes an automatic Mall elevator control system that uses an infrared sensor and microcontroller to automatically turn the elevator lights on when someone enters and off when they leave to save power. It includes block diagrams of the system components, detailed circuit diagrams and explanations of the infrared transmitter, receiver, microcontroller, and power supply circuits. The system aims to save electrical power by automatically controlling the elevator lights based on occupancy.
Bluetooth Home Automation
I made this project soon after completing my trainee period. This project was aimed at reducing human effort and allowing ease of access to differently-abled people. Home automation using bluetooth is really cheap to build and easy install in your home.
automatic room lightening system
This document summarizes an automatic room lighting system project created by students. The system uses a PIR motion sensor to detect movement and signal an Arduino board. When motion is detected, the Arduino activates a relay module to turn on an LED light. Without motion, the light will turn off. The document outlines the components, circuit diagram, working principle, simulation code, and applications of the system for automatically controlling lights and saving energy.
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Slide for brain controlled artificial leg
- 1. BRAIN CONTROLLED ARTIFICIAL LEGS Presented by, S . SIVAKUMAR III-ECE KONGUNADU COOLLEGE OF ENGINNERINGANDTECHNOLOGY
- 2. INTRODUCTION: Brain computer interface. It is a direct communication path between a human brain or animal brain and external device.
- 3. BRAIN WAVES There are four categories Beta waves(15-40 c/sec) Alpha waves(9-14 c/sec) Theta waves(5-8 c/sec) Delta waves(1.5-4 c/sec)
- 5. ELECTRODE CAP • It contains electrodes which are placed on the skull in an arrangement called 10-20 system. • Main function of the electrode cap is to take the brain signals in the form of electrical signals
- 6. AMPLIFIER Output signal from the electrode cap will be in the range of milli volt & microvolt Hence there is a need for amplification ADC Output signals are analog in nature So the signals are sent to ADC to convert the analog signals to the digital signals
- 7. SIGNAL PROCESSOR Using the ouput signal from the a/d conv. Parameter extraction, pattern classification & pattern identification are done. Then the signal is fed to FFT unit for simplifying the calculations MICROCONTROLLER UNIT It performs the robotic operations with the help of stepper motor It will control the operations like walking, running etc.
- 8. Appearance of artificial legs
- 9. POWER SUPPLY • It uses Li-ion battery • It require to charge once in 2days • The life time will be longer when compared to other batteries
- 10. DIFF. BETWEEN NORMAL AND BRAIN CONTROLLED ARTIFICIAL LEGS Brain Controlled Artificial Legs Normal Artificial Legs 1. Ease of Construction 1. Complex in construction 2.Cost is not more than Rs.5,00,000 2. Cost is about $80,000- $90,000(Rs.35,00,000 to Rs.40,00,000) 3.User can have full control over the artificial leg. 3. User cannot have full control over the artificial leg. 4.Semi-Automatic 4. Fully Automatic 5.Sensors are absent. 5.Sensors are present 6.Requires simple control unit. 6. Requires complex control unit.
- 11. conclusion • The performance of the proposed system will be better than the existing artificial legs • With the system life can be made easier for the differently abled persons
- 12. QUERIES ?