Literature DB >> 29877820

A Multimodal Adaptive Wireless Control Interface for People With Upper-Body Disabilities.

Cheikh Latyr Fall, Francis Quevillon, Martine Blouin, Simon Latour, Alexandre Campeau-Lecours, Clement Gosselin, Benoit Gosselin.   

Abstract

This paper describes a multimodal body-machine interface (BoMI) to help individuals with upper-limb disabilities using advanced assistive technologies, such as robotic arms. The proposed system uses a wearable and wireless body sensor network (WBSN) supporting up to six sensor nodes to measure the natural upper-body gesture of the users and translate it into control commands. Natural gesture of the head and upper-body parts, as well as muscular activity, are measured using inertial measurement units (IMUs) and surface electromyography (sEMG) using custom-designed multimodal wireless sensor nodes. An IMU sensing node is attached to a headset worn by the user. It has a size of 2.9 cm 2.9 cm, a maximum power consumption of 31 mW, and provides angular precision of 1. Multimodal patch sensor nodes, including both IMU and sEMG sensing modalities are placed over the user able-body parts to measure the motion and muscular activity. These nodes have a size of 2.5 cm 4.0 cm and a maximum power consumption of 11 mW. The proposed BoMI runs on a Raspberry Pi. It can adapt to several types of users through different control scenarios using the head and shoulder motion, as well as muscular activity, and provides a power autonomy of up to 24 h. JACO, a 6-DoF assistive robotic arm, is used as a testbed to evaluate the performance of the proposed BoMI. Ten able-bodied subjects performed ADLs while operating the AT device, using the Test d'Évaluation des Membres Supérieurs de Personnes Âgées to evaluate and compare the proposed BoMI with the conventional joystick controller. It is shown that the users can perform all tasks with the proposed BoMI, almost as fast as with the joystick controller, with only 30% time overhead on average, while being potentially more accessible to the upper-body disabled who cannot use the conventional joystick controller. Tests show that control performance with the proposed BoMI improved by up to 17% on average, after three trials.

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Year:  2018        PMID: 29877820     DOI: 10.1109/TBCAS.2018.2810256

Source DB:  PubMed          Journal:  IEEE Trans Biomed Circuits Syst        ISSN: 1932-4545            Impact factor:   3.833


  6 in total

1.  Assisted Grasping in Individuals with Tetraplegia: Improving Control through Residual Muscle Contraction and Movement.

Authors:  Lucas Fonseca; Wafa Tigra; Benjamin Navarro; David Guiraud; Charles Fattal; Antônio Bó; Emerson Fachin-Martins; Violaine Leynaert; Anthony Gélis; Christine Azevedo-Coste
Journal:  Sensors (Basel)       Date:  2019-10-18       Impact factor: 3.576

2.  Personalized Smart Clothing Design Based on Multimodal Visual Data Detection.

Authors:  Haijuan Deng; Minglong Liu
Journal:  Comput Intell Neurosci       Date:  2022-03-24

3.  Control of a Wheelchair-Mounted 6DOF Assistive Robot With Chin and Finger Joysticks.

Authors:  Ivan Rulik; Md Samiul Haque Sunny; Javier Dario Sanjuan De Caro; Md Ishrak Islam Zarif; Brahim Brahmi; Sheikh Iqbal Ahamed; Katie Schultz; Inga Wang; Tony Leheng; Jason Peng Longxiang; Mohammad H Rahman
Journal:  Front Robot AI       Date:  2022-07-22

4.  Design and Implementation of a Position, Speed and Orientation Fuzzy Controller Using a Motion Capture System to Operate a Wheelchair Prototype.

Authors:  Mauro Callejas-Cuervo; Aura Ximena González-Cely; Teodiano Bastos-Filho
Journal:  Sensors (Basel)       Date:  2021-06-25       Impact factor: 3.576

5.  Smart Assistive Architecture for the Integration of IoT Devices, Robotic Systems, and Multimodal Interfaces in Healthcare Environments.

Authors:  Alberto Brunete; Ernesto Gambao; Miguel Hernando; Raquel Cedazo
Journal:  Sensors (Basel)       Date:  2021-03-22       Impact factor: 3.576

Review 6.  Using Inertial Sensors to Determine Head Motion-A Review.

Authors:  Severin Ionut-Cristian; Dobrea Dan-Marius
Journal:  J Imaging       Date:  2021-12-06
  6 in total

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