Development of EMG Controlled Electric Wheelchair Using SVM and kNN Classifier for SCI Patients

2019 ◽  
pp. 75-83 ◽  
Author(s):  
Bhupender Kumar ◽  
Yogesh Paul ◽  
Ram Avtar Jaswal
Keyword(s):  
Electric Wheelchair ◽  
Knn Classifier

AUTOMATIC HEAD-MOVEMENT CONTROLLED WHEELCHAIR

2020 ◽  
Vol 9 (10) ◽  
pp. 62-67
Keyword(s):  
Head Movement ◽  
Motion Sensor ◽  
Electric Wheelchair ◽  
Wheel Chair ◽  
Head Band

This project is regarding the Motion controlled wheelchair for disabled. We are going to control motorized wheelchair using a head band having motion sensor and Arduino as controller. Problem: “often disabled who cannot walk find themselves being burden for their families or caretakers just for moving around the house. Disabled who are paralysed below head, who may not have functioning arms cannot control joystick controlled electric wheelchair.” This project is to solve their problem using a motion sensor to control their wheelchair. We are aiming towards building a more affordable, unique, low maintenance and available for all kind of head-controlled wheel chair.

scholarly journals Data Reduction in the String Space for Efficient kNN Classification Through Space Partitioning

2020 ◽  
Vol 10 (10) ◽  
pp. 3356 ◽  
Author(s):  
Jose J. Valero-Mas ◽  
Francisco J. Castellanos
Keyword(s):  
Data Reduction ◽  
Structural Data ◽  
Data Representation ◽  
Space Partitioning ◽  
Classification Rate ◽  
Symbolic Data ◽  
Knn Classifier ◽  
Initial Dataset ◽  
Low Efficiency ◽  
High Level

Within the Pattern Recognition field, two representations are generally considered for encoding the data: statistical codifications, which describe elements as feature vectors, and structural representations, which encode elements as high-level symbolic data structures such as strings, trees or graphs. While the vast majority of classifiers are capable of addressing statistical spaces, only some particular methods are suitable for structural representations. The kNN classifier constitutes one of the scarce examples of algorithms capable of tackling both statistical and structural spaces. This method is based on the computation of the dissimilarity between all the samples of the set, which is the main reason for its high versatility, but in turn, for its low efficiency as well. Prototype Generation is one of the possibilities for palliating this issue. These mechanisms generate a reduced version of the initial dataset by performing data transformation and aggregation processes on the initial collection. Nevertheless, these generation processes are quite dependent on the data representation considered, being not generally well defined for structural data. In this work we present the adaptation of the generation-based reduction algorithm Reduction through Homogeneous Clusters to the case of string data. This algorithm performs the reduction by partitioning the space into class-homogeneous clusters for then generating a representative prototype as the median value of each group. Thus, the main issue to tackle is the retrieval of the median element of a set of strings. Our comprehensive experimentation comparatively assesses the performance of this algorithm in both the statistical and the string-based spaces. Results prove the relevance of our approach by showing a competitive compromise between classification rate and data reduction.

scholarly journals Electric Wheelchair Using Blynk Smartphone Application

2021 ◽  
Vol 794 (1) ◽  
pp. 012124
Author(s):  
F A Nadjib ◽  
H P Sihombing ◽  
J Linggarjati ◽  
R Hedwig
Keyword(s):  
Smartphone Application ◽  
Electric Wheelchair

Fuzzy-EKF Controller for Intelligent Wheelchair Navigation

2016 ◽  
Vol 25 (2) ◽  
pp. 107-121 ◽  
Author(s):  
Malek Njah ◽  
Mohamed Jallouli
Keyword(s):  
Kalman Filter ◽  
Control System ◽  
Energy Management ◽  
Research Laboratory ◽  
Control Method ◽  
Severe Disabilities ◽  
Indoor Navigation ◽  
Electric Wheelchair ◽  
Security Environment ◽  
Intelligent Wheelchair

AbstractThe electric wheelchair gives more autonomy and facilitates movement for handicapped persons in the home or in a hospital. Among the problems faced by these persons are collision with obstacles, the doorway, the navigation in a hallway, and reaching the desired place. These problems are due to the difficult manipulation of an electric wheelchair, especially for persons with severe disabilities. Hence, we tried to add more functionality to the standard wheelchair in order to increase movement range, security, environment access, and comfort. In this context, we have developed an automatic control method for indoor navigation. The proposed control system is mounted on the electric wheelchair for the handicapped, developed in the research laboratory CEMLab (Control and Energy Management Laboratory-Tunisia). The proposed method is based on two fuzzy controllers that ensure target achievement and obstacle avoidance. Furthermore, an extended Kalman filter was used to provide precise measurements and more effective data fusion localization. In this paper, we present the simulation and experimental results of the wheelchair navigation system.

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