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Brain Wave Controlled Wheelchair

Assistive Robotics

A smart wheelchair controls movement
using brainwaves, touch, voice, or gestures offering obstacle-free mobility, smart home control, and greater independence.

Vector (2)-da6325

Institute:
Institute of Information Technology, Mandi

Vector (3)-42d8ac

PI Name:
Prof. Laxmidhar Behera

Technology Readiness Level (TRL)
4

Intellectual Property:
PA No. 202311000340

Problem
Addressed

Mobility aids are essential, but most options are either basic or unaffordable. In India. only 10% of people have access to wheelchairs, and existing models lack flexibility. The proposed prototypes offers an affordable solution with multimodal controls (Brain control interface (BCD, touch, gesture, voice) and home automation integration. It provides customizable mobility. improving independence and quality of life for individuals with disabilities, while reducing reliance on caregivers.
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About the
Technology

  • The Brainwave-controlled wheelchair transforms a manual wheelchair into an autonomous system with Al-powered obstacle avoidance for smooth navigation.
  • It offers customizable multimodal controls (BCI, touch, gesture, voice) to suit diverse user needs and integrates home automation for greater independence.
  • This cost-effective smart wheelchair enhances accessibility. empowering users with improved mobility and autonomy.
  • Autonomous navigation with advanced obstacle avoidance and safety features. Multimodal inputs: Brain-wave, touch, gesture, voice, and joystick, offering flexible control options. Affordable design. making the smart wheelchair accessible to a wider population.
  • Integrates home automation, enabling control of household devices directly from the wheelchair.

Application Areas & Use Cases

  • Assists stroke patients, Motor Neuron Disease (MND) patients, and the elderly.
  • Enhances mobility and independence with home automation.
  • Supports navigation in crowded spaces.
  • Enables control of household devices for convenience
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Product Dimensions and Maximum Payload 108 x 68 x 93 cm; 100 kg
Speed, Battery and Power 0.5 m/sec, Lead Acid battery. 20AH Battery, 2-4 km per Charge
Control Interface Brain-Signal interface, Touch, Voice and gesture control
Sensors for Navigation Depth Cameras for visual monitoring and LiDAR for autonomous navigation and obstacle
Brain Control Interface Headset Dry electrode based headset and wireless model
Communication and User Interface Touchscreen displays for manual controls, Voice interaction via microphones and speakers.
Home automation 4-device control at a time
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