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Proceedings ArticleDOI: 10.1109/ICVES.2009.5400323

A smart mobility solution for physically challenged

01 Nov 2009-pp 168-173
Abstract: This paper presents a hand gesture and a vision driven wheelchair system for physically handicapped people. The system is contrived to have a utilitarian design that caters to most of the disabilities rather than just one. In order to minimize system-human interaction, we have endeavored to present two distinct but closely related concepts viz. the hand gesture and vision based control system in conjunction for the wheelchair control. The wheelchair system is designed such that it provides for a natural and an intuitive user interface which can comprehend and react to in compliance with the users' instinctive volition which eases the mobility of the physically challenged people. All image processing was performed using NI Vision Assistant. NI LabVIEW was used to train and implement Neural Networks for Hand Gesture Classification and also to enable motion control. A prototype was developed on which all our experiments were successfully carried out. The system has been tested for users with varied hand shapes and proved to be extremely reliable. more

Topics: Wheelchair (54%), User interface (50%)

Open accessBook
01 Jan 1994-

607 Citations

Journal ArticleDOI: 10.1109/JSEN.2016.2585582
Abstract: This paper presents a novel and simple hand gesture recognition method to be used in rehabilitation of people who have mobility issues particularly stroke patients and patients with spinal cord injury (SCI). Keeping in mind the reach of such a system for a wider community of people with mobility issues, the proposed low-cost control device called gpaD—gesture pad provides an alternative solution to the joystick-based powered wheelchair control through hand gestures. In this method, IR sensors are used for identifying the simple gestures to control the powered wheelchair to move in any direction. In the proposed prototype system HanGes, a gesture pad that includes IR sensors, MCU and power management circuit is designed for gesture recognition and identification and a controller for driving motors is implemented. HanGes’s design, implementation, the response time calculations of the system, testing, performance evaluation with stroke and SCI patients are discussed in detail. With the average success rate of gesture recognition above 99.25% and response time as comparable with that of commercially available joystick controlled wheelchair, HanGes could be a possible alternative to the existing ones. With extensive experiments that demonstrate the accuracy of the system, the user experience, testing with patients, and the implementation cost indicate the superiority of our system. more

Topics: Gesture recognition (62%), Wheelchair (57%), Joystick (52%) more

17 Citations

Proceedings ArticleDOI: 10.1109/GHTC.2012.83
21 Oct 2012-
Abstract: Various research studies conducted all around the world reveal that 75% of people with debilitating physical disabilities and elderly people experience significant difficulties for their day to day locomotion. Although there are existing solutions to overcome this problem, none of them served to be customizable, economical and user friendly all at the same time. Therefore, one of the best options that could be useful for these affected class of people is a gesture-based interaction with their environment, in particular their wheelchairs. The proposed system named as 'Gest-BOT', uses a small camera mounted very close to the user's hand, which tracks the small movements of their fingers to understand the direction of movement of the wheelchair. A gesture recognition system which identifies the gesture is then interfaced to the wheelchair control system in order move it to the desired location. Gest-BOT is effortless to use, customizable, economical, highly convenient and non-intrusive. The hardware implementation of Gest-BOT consists of a wheelchair, an Arduino board based ATmega microcontroller and an Intel Atom EBC-352 processor, which uses MATLAB® executables for gesture image processing. We have also calculated the response of the system under various conditions which is detailed in the paper. more

Topics: Gesture recognition (59%), Wheelchair (54%), Arduino (50%)

10 Citations

Journal ArticleDOI: 10.1080/03091902.2016.1210685
Sharmila Ashok1Institutions (1)
Abstract: A vital perception in designing human-machine interfaces for people with disabilities is hands-free control. It is important in setting up communication among a machine and the part of human body. Nowadays, hands-free control is extensively used to help disabled people to control the wheelchair. The hands-free control functions are not only helpful to elderly and disabled, but also useful for normal people who might require using their hands for other tasks at the same time. As a result, normal people are capable of manipulating multiple tasks at the same time. The wheelchair is manoeuvred using brainwaves, eyes and facial muscles movements, voice, tongue, gesture. The mobility using a powered wheelchair improves the quality of life of the aged people and the people with mobility impairments significantly. These powered wheelchairs can be actuated using various high-level control interfaces. In this review, the use of natural biological signals and non-biological signal to do the hands-free control of powered wheelchair is presented in this article. more

Topics: Wheelchair (64%)

9 Citations

Open accessProceedings Article
Yong Hee Jung1, Shengeng Qin1Institutions (1)
21 Nov 2011-
Abstract: Present smart phones contain high-tech sensors to monitor three-dimensional movements of the device and users' behaviours. These sensors allow mobile devices to recognize motion gestures. However, only a few gesture sets have been created, and little is known about best practices in motion-gesture design. Also, the created gesture sets were generated from people who do not have to use their motion gestures very much in their daily lives, not from people with communication difficulties. To address this issue, we use a focus group that has dyslexia and other specific learning difficulties for designing the user-defined gesture sets. This paper presents the results of our study that elicits the focus group's gestures to invoke commands on a smart-phone device. It demonstrates how the gesture sets have been designed and finalised throughout other research activities, such as observation and interviews. Finally, we suggest that our result would help people with communication impairments conveniently interact with others in an intuitive and socially acceptable manner. more

Topics: Gesture recognition (64%), Gesture (60%), Mobile device (51%)

2 Citations


Journal ArticleDOI: 10.1038/SCIENTIFICAMERICAN0991-94
Abstract: Specialized elements of hardware and software, connected by wires, radio waves and infrared, will soon be so ubiquitous that no-one will notice their presence. more

Topics: Ubiquitous robot (50%)

8,840 Citations

Journal ArticleDOI: 10.1109/TIT.1962.1057692
Ming-Kuei Hu1Institutions (1)
Abstract: In this paper a theory of two-dimensional moment invariants for planar geometric figures is presented. A fundamental theorem is established to relate such moment invariants to the well-known algebraic invariants. Complete systems of moment invariants under translation, similitude and orthogonal transformations are derived. Some moment invariants under general two-dimensional linear transformations are also included. Both theoretical formulation and practical models of visual pattern recognition based upon these moment invariants are discussed. A simple simulation program together with its performance are also presented. It is shown that recognition of geometrical patterns and alphabetical characters independently of position, size and orientation can be accomplished. It is also indicated that generalization is possible to include invariance with parallel projection. more

Topics: Image moment (60%), Moment (mathematics) (58%), Invariant theory (51%) more

7,602 Citations

Open accessBook
01 Dec 2003-
Abstract: 1. Introduction. 2. Fundamentals. 3. Intensity Transformations and Spatial Filtering. 4. Frequency Domain Processing. 5. Image Restoration. 6. Color Image Processing. 7. Wavelets. 8. Image Compression. 9. Morphological Image Processing. 10. Image Segmentation. 11. Representation and Description. 12. Object Recognition. more

Topics: Digital image processing (75%), Image processing (74%), Standard test image (70%) more

6,204 Citations

Open accessJournal Article
Abstract: Specialized elements of hardware and software, connected by wires, radio waves and infrared, will soon be so ubiquitous that no-one will notice their presence more

Topics: Radio wave (54%), Notice (52%), Software (50%)

4,954 Citations

Open accessJournal Article

2,457 Citations

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