Department Publications

A sense of independence is critical for individuals with mobility impairments, with stair negotiation remaining one of the most demanding daily tasks. This article presents a novel track-based stair-climbing mechanism inspired by leech locomotion, designed to enhance adaptability to varying staircase geometries. The mechanism emulates leech-like motion during both ascent and descent, decomposing each maneuver into multiple segments to ensure stable posture and safety. Throughout motion, the mechanism maintains a large contact surface with the stairs, improving stability. Simulation and experimental studies validate the effectiveness of the proposed motion, particularly during transitions at the top and bottom of the staircase. Results demonstrate that the motion profile reduces abrupt movements and improves user comfort during stair-climbing operation.

As Virtual Reality (VR) technology continues to advance and widespread through various industries, the potential of immersive technologies in the banking sector has also begun to be acknowledged more commonly. VR banking, a 3D bank environment developed in an immersive world to provide customers with bank services, has the potential to substantially enhance the customer experience. However, a clear insight into an end-to-end pipeline for developing a banking system in VR is yet to be presented. This paper presents a novel VR banking system that facilitates users with personalized full-body avatars for representation within a VR bank, a speech-to-text integration for providing user information for bank services, and real-time dual avatar interaction and communication with a bank employee. Through a subjective survey, we evaluate the performance of the proposed facilitates and the overall VR bank …

This research paper presents a novel track based stair-climbing wheelchair design with improved stability and performance. The proposed design has an adaptable arrangement to the staircase especially at the top of the staircase. In the existing wheelchair designs, this particular feature has not been adequately addressed. The proposed design consists of body frame and supporting rubber track arms. Of the two main operations; ascending and descending, the most critical operations is at the top of the staircase, which is smoothly controlled by following the staircase profile. This motion is achieved by properly synchronizing the rubber track arms according to a pre-planned motion profile. As a result, user does not feel sudden motions in position and attitude. Furthermore, the proposed wheelchair is adaptable to any staircase.

There are several systems that use one or several Kinect sensors for human gait analysis, particularly for diagnosis of patients. However, due to the limited depth sensing range of the Kinect—a sensor manufactured for video gaming—the depth measurement accuracy reduces with distance from the Kinect. In addition, self-occlusion of the subject limits the accuracy and utility of such systems. We overcome these limitations by using a two-Kinect gait analysis system and mechanically moving the Kinects in synchronization with the test subject and each other. This increases the practical measurement range of the Kinect-based system whilst maintaining the measurement accuracy. Results of the comparison of knee flexion, step length, and stride length with a software based method show that our moving Kinect system can accurately analyse these gait parameters.

Human gait analysis, the study of human locomotion, is possible with low-cost RGBD sensors such as the Kinect sensor. However, due to the inherent depth sensing accuracy limitations of these sensors as the distance from the sensor increases, the distance range of gait analysis too becomes small and inefficient for clinical use. We present a system that uses two independent Kinects in a data fusion framework that increases the distance range of gait analysis from 2.5 m to 4 m with three gait cycles. Our gait parameters are reasonably accurate and comparable with existing systems with 4% error in length measurements and 5° error in flexion measurements. The system is extensible to have several Kinects.

The P300 Speller is a Brain Computer Interface that enables communication using the EEG signal. The P300 wave is an Event Related Potential that occurs as a response to a familiar stimulus. This system can be used to aid persons who are unable to communicate via conventional methods. In this paper, the P300 Speller has been modified to allow communication in three languages: English, Sinhala and Tamil. Classification of the P300 waveform was done using an ensemble of Support Vector Machines. A mean letter classification accuracy of 83.76% and a mean P300 classification accuracy of 90.68% was achieved on our dataset.

We present a sensor platform to be mounted on the white cane used by the visually impaired. This can estimate the direction of user movement and enable the user to detect obstacles lying on the path in advance. The sensor platform contains an ultrasonic sensor and an IMU (Inertia Measurement Unit). We develop a model to estimate distances to obstacles in the path and their width based on sensor measurements. The model is demonstrated to have an overall accuracy of 84%, with accuracy as high as 90% for obstacles within 50cm in front of the user. Knowledge of obstacle locations and their size in advance, would enable us to guide visually impaired persons to deviate from their path and return to it after the obstacle has been passed.

Brain-Computer Interaction (BCI) is a technology developed with the purpose of building a pathway between the brain and computer which is independent of neuromuscular functions. Potential applications in rehabilitation of patients with motor disabilities and video gaming make BCI an important field of research. A task like controlling a prosthetic limb using BCI is challenging. Performing this with readily available consumer grade EEG devices complicates the matters further due to lower accuracies. This paper presents the work related to an online classifier for imagined hand movement implemented using Emotiv Epoc for EEG data capturing. The system attempts to discriminate between left and right hand movement imagination by analysing the recordings of two electrodes placed over the motor-cortex. Auto-Regression (AR) based signal processing techniques are employed to derive features that enable …

Safety of critically ill patients in intensive care units is an important aspect of medical care. There are many factors contributing to shortcomings and errors in patient care in the intensive care setting, such as long working hours, high levels of stress, lack of enough people, may cause human errors and affecting the effectiveness of the decisions of the physician. Several attempts have been made to increase the effectiveness of such decisions by issuing early alerts on adverse patient conditions. However, such alerts are based on single parameter variations but not on the relationship between multiple parameter variations. Thus, inability to provide an effective communication model causes a considerable bottleneck in intensive care unit (ICU) operations. The proposed model is an integrated solution which identifies the adverse patient conditions on multiple parameter variations and then provides predictive treatment …

The safety of critically ill patients in intensive care units is an important aspect of medical care. Many human factors contribute to deficiencies and errors in patient care in the intensive care setting, such as long working hours, high levels of stress, lack of enough people, may cause human errors and affecting the effectiveness of the decisions of the physician. Several attempts have been made to increase the effectiveness of such decisions by issuing early alerts on adverse patient conditions. However, such alerts are based on single parameter variations, and not on the relationship between multiple parameter variations. We developed a computer-based model is an integrated solution which identifies adverse patient events based on multiple parameter variations, and then provides predictive treatment suggestions based on the likely clinical conditions which result in the parameter variations. The proposed system follows an interactive communication cycle in order to properly notify the responsible treating physicians at different tiers of responsibility. Our model is capable of early identification of adverse conditions and providing suitable treatment suggestions, thus acting as a decision support system to assist the treating physician.

In this paper EOG signal processing and developing a low cost signal interface for wheelchair with high accuracy and reliability for severely disabled people is presented. Here the signal processing is done on a microcontroller which reduces the cost drastically rather than using a computer. Eye movement is detected by processing EOG signal, and associates the eye movement to motion commands of the wheelchair such as forward, reverse, left and right. A 99% accurate classification has been demonstrated experimentally.

In this paper, we present a novel strategy to detect the slipping of an object grasped by a human hand. The recognition of slipping of a grasped object early plays a significant role in designing the dexterous robotic hands to ensure a firm grasping. Here, we present a system that uses force sensors embedded in a tight glove to capture force variations during a slipping of a grasped object. The analysis of contribution by five fingers and the palm for grasping is presented based on new factor called contribution factor. Also, we propose a new direction to incorporate controlling of dexterous robot hands based on spatial activity of force exerted by hand to ensure a firm grasping.

In this work, we propose a framework that can provide performance metrics with regards to the usability of an assistive device designed to provide visual servoing of a reaching task performed by a visually impaired individual. The framework provides a model and methodology from which performance metrics can be synthesized based on robotic manipular kinematics and an adaptation of Fitts' law for reaching task motions in a 3D environment. The purpose of which is to facilitate an understanding of how well the system's design accommodates the user's natural movement style when performing the reaching task. Use of advances in visual tracking techniques employing scale, view-point, and illumination invariant features are incorporated to allow for a further decoupling of the feature space from the joint-level control space.

In this paper, a semiautonomous low-cost wheelchair robot to supplement impaired mobility of handicapped or elderly people is presented. The motion of the wheelchair is controlled by the joystick and the sonar sensor in such a manner that the sonar sensor has higher priority than joystick in normal conditions. The wheelchair uses two permanent magnet DC motors which are differentially driven using pulse width modulation (PWM) control signals. The motors drive the worm to drive the wheelchair. The semiautonomous wheelchair is equipped with four ultrasonic range finders in the front, one at the back to avoid the obstacles in its path and another one near the foot rest to detect steps. The system totally uses six ultrasonic sensors. The semiautonomous wheelchair was successfully tested under various conditions and satisfactory results were obtained.

In this work, we have taken the first step towards the creation of a computerized seeing-eye guide dog. The system we presented extends the development of assistive technology for the visually impaired into a new area: object tracking and visual servoing. The system uses computer vision to provide a kind of surrogate sight for the human user; sensing information from the environment and communicating it through haptic signalling. Our proof-of concept prototype is a low-cost wearable system which uses a colour camera to analyze a scene and recognize a desired object, then generate tactile cues to the wearer to steer his or her hand towards the object. We have proved the system in trials with random users in an unstructured environment.

Abstract< BR> Ⅰ. INTRODUCTION< BR> Ⅱ. MOTION PLANNING AND CONTROL OF ROBOT< BR> Ⅲ. TELEOPERATION AND SUPERVISORY CONTROL< BR> Ⅳ. WELFARE TELEROBOTIC SYSTEM< BR> Ⅴ. RESULTS AND DISCUSSION< BR> Ⅵ. CONCLUSION< BR> ACKNOWLEDGEMENTS< BR> REFERENCES< BR> APPENDIX: BASIC STEPS OF MOTION PLANNING< BR>

The paper describes several digital signal processing (DSP) techniques used in the development of a computer-based speech trainer for hearing impaired children. Children with congenital hearing impairments have difficulties in speaking, and even in making the basic sounds associated with speech. Speech therapists use specialized training methods to train such children. The dearth of qualified speech therapists, and other facilities hinder the speech development of many children in need of such training in Sri Lanka. The speech trainer described in this paper was developed as an alleviation to the above problem. The training tool developed, will aid a child with initial guidance from an adult, to master the pronunciation of initial sounds taught in a speech therapy programme, in a game-like environment. In its current status, the training tool can guide children in pronouncing the five vowel sounds, the first step in …

The paper describes the development of a speech trainer based on digital signal processing (DSP) techniques, for hearing impaired children. The DSP techniques investigated in the implementation of this software-based speech trainer, the final" product'and its degree of success in actual use are highlighted. Children with congenital hearing impairments have difficulties in speaking, and even in making the basic sounds associated with speech. Speech therapists use specialized training methods to train such children. The first step in such programs is the training of the pronunciation of common sounds. The dearth of qualified speech therapists, and other facilities hinder the speech development of many children in need of such training.