Publications by authors named "Chakaveh Ahmadizadeh"

Textile sensors transform our everyday clothing into a means to track movement and biosignals in a completely unobtrusive way. One major hindrance to the adoption of "smart" clothing is the difficulty encountered with connections and space when scaling up the number of sensors. There is a lack of research addressing a key limitation in wearable electronics: Connections between rigid and textile elements are often unreliable, and they require interfacing sensors in a way incompatible with textile mass production methods.

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Monitoring human movement is highly relevant in mobile health applications. Textile-based wearable solutions have the potential for continuous and unobtrusive monitoring. The precise estimation of joint angles is important in applications such as the prevention of osteoarthritis or in the assessment of the progress of physical rehabilitation.

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Background: Assistive robotic hand orthoses can support people with sensorimotor hand impairment in many activities of daily living and therefore help to regain independence. However, in order for the users to fully benefit from the functionalities of such devices, a safe and reliable way to detect their movement intention for device control is crucial. Gesture recognition based on force myography measuring volumetric changes in the muscles during contraction has been previously shown to be a viable and easy to implement strategy to control hand prostheses.

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Mobile health technology and activity tracking with wearable sensors enable continuous unobtrusive monitoring of movement and biophysical parameters. Advancements in clothing-based wearable devices have employed textiles as transmission lines, communication hubs, and various sensing modalities; this area of research is moving towards complete integration of circuitry into textile components. A current limitation for motion tracking is the need for communication protocols demanding physical connection of textile with rigid devices, or vector network analyzers (VNA) with limited portability and lower sampling rates.

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Various human machine interfaces (HMIs) are used to control prostheses, such as robotic hands. One of the promising HMIs is Force Myography (FMG). Previous research has shown the potential for the use of high density FMG (HD-FMG) that can lead to higher accuracy of prosthesis control.

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The pressure map at the interface of a prosthetic socket and a residual limb contains information that can be used in various prosthetic applications including prosthetic control and prosthetic fitting. The interface pressure is often obtained using force sensitive resistors (FSRs). However, as reported by multiple studies, accuracies of the FSR-based pressure sensing systems decrease when sensors are bent to be positioned on a limb.

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