Machine Intelligence & Bio-Motion Research Lab

About Us

"We focus on the development of a multi-modal gait analysis system using vision sensors such as Microsoft Kinect and wearable sensors namely Inertial Measurement Unit (IMU), Electromyography (EMG), and Electroencephalography (EEG) sensors. The objective of our research is to build an affordable and efficient gait analysis tool that can be used for health care applications in our daily lives using advanced machine learning techniques such as convolutional neural networks, recurrent neural networks etc. "

Research Work

Gait Analysis using MULtiPLE Kinect v2.0

Gait analysis using EMOtiv Epoch+ headset, Kinect

Development of pathological gait detection system in multi-Kinect environment.

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Gait analysis using EMOtiv Epoch+ headset, Kinect

Modelling and understanding of human cognitive states using gait signature.

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GAIT Analysis using WEARABLE sensor

Gait analysis using EMOtiv Epoch+ headset, Kinect

GAIT Analysis using WEARABLE sensor

Modelling and analyzing abnormal human gait using wearable sensors such as IMU sensor.

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human-robot INTERACTION

Human Gesture Recognition using machine learning techniques

Cognitive state estimation using EMOTIV EPOCH+ Headset

Understanding Human Cognition for Modelling and Controlling Humanoid Robot Behavior.

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Cognitive state estimation using EMOTIV EPOCH+ Headset

Human Gesture Recognition using machine learning techniques

Cognitive state estimation using EMOTIV EPOCH+ Headset

Estimation of Human Cognitive States through Ambulatory EEG signal Analysis

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Human Gesture Recognition using machine learning techniques

Indian Sign Language (ISL) classification using RGB-D images from Kinect V2.0

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