Seat Movement Type Inverse Pendulum Control Wheel Chair Robot

2002 ◽  
Vol 2002.8 (0) ◽  
pp. 377-378
Author(s):  
Otsushiro Tsubouchi ◽  
Yoshihiko Takahashi
Keyword(s):  
Movement Type ◽  
Wheel Chair ◽  
Control Wheel

Automatic Wheel Chair Control Using Eyeball Movement for Physically Challenged People

2012 ◽  
Vol 3 (3) ◽  
pp. 317-319
Author(s):  
R.Venkatesh R.Venkatesh ◽  
◽  
R.Karthick R.Karthick
Keyword(s):  
Wheel Chair ◽  
Physically Challenged

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.

Measurement of the dynamic forces during manual wheel chair propulsion

1992 ◽  
Vol 25 (6) ◽  
pp. 677 ◽  
Author(s):  
Mark G. Strauss ◽  
Jerry Maloney ◽  
Frank Ngo ◽  
Matthew Phillips
Keyword(s):  
Dynamic Forces ◽  
Wheel Chair

scholarly journals Investigating the Intervention Parameters of Endogenous Paired Associative Stimulation (ePAS)

2021 ◽  
Vol 11 (2) ◽  
pp. 224
Author(s):  
Gemma Alder ◽  
Nada Signal ◽  
Alain C. Vandal ◽  
Sharon Olsen ◽  
Mads Jochumsen ◽  
...  
Keyword(s):  
Neural Plasticity ◽  
Repeated Measures ◽  
Single Pulse ◽  
Stroke Recovery ◽  
Motor Threshold ◽  
Additive Interaction ◽  
Post Intervention ◽  
Paired Associative Stimulation ◽  
Intervention Efficacy ◽  
Movement Type

Advances in our understanding of neural plasticity have prompted the emergence of neuromodulatory interventions, which modulate corticomotor excitability (CME) and hold potential for accelerating stroke recovery. Endogenous paired associative stimulation (ePAS) involves the repeated pairing of a single pulse of peripheral electrical stimulation (PES) with endogenous movement-related cortical potentials (MRCPs), which are derived from electroencephalography. However, little is known about the optimal parameters for its delivery. A factorial design with repeated measures delivered four different versions of ePAS, in which PES intensities and movement type were manipulated. Linear mixed models were employed to assess interaction effects between PES intensity (suprathreshold (Hi) and motor threshold (Lo)) and movement type (Voluntary and Imagined) on CME. ePAS interventions significantly increased CME compared to control interventions, except in the case of Lo-Voluntary ePAS. There was an overall main effect for the Hi-Voluntary ePAS intervention immediately post-intervention (p = 0.002), with a sub-additive interaction effect at 30 min’ post-intervention (p = 0.042). Hi-Imagined and Lo-Imagined ePAS significantly increased CME for 30 min post-intervention (p = 0.038 and p = 0.043 respectively). The effects of the two PES intensities were not significantly different. CME was significantly greater after performing imagined movements, compared to voluntary movements, with motor threshold PES (Lo) 15 min post-intervention (p = 0.012). This study supports previous research investigating Lo-Imagined ePAS and extends those findings by illustrating that ePAS interventions that deliver suprathreshold intensities during voluntary or imagined movements (Hi-Voluntary and Hi-Imagined) also increase CME. Importantly, our findings indicate that stimulation intensity and movement type interact in ePAS interventions. Factorial designs are an efficient way to explore the effects of manipulating the parameters of neuromodulatory interventions. Further research is required to ensure that these parameters are appropriately refined to maximise intervention efficacy for people with stroke and to support translation into clinical practice.

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