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Riasat IslamMember status icon

Post-Doctoral Research Associate
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The SENSE project is a novel initiative aimed at enhancing sensory exploration of nature through cutting-edge technology. The project involves testing a haptic device that has been integrated with a web application containing textures from nature such as fur, scales, tree barks, and bees.

This haptic device offers a unique and interactive way for school kids to experience and learn about the textures of nature in a hands-on manner. The web application is designed to be user-friendly, allowing children to navigate and explore the different textures with ease.

The project also involves using the think-aloud protocol to gather data and feedback from the children as they use the haptic device and web application. The data collected will be analysed to further refine and improve the SENSE project, making it an even more valuable tool for sensory exploration and education.

The SENSE project has the potential to revolutionize the way children learn about and experience nature, and we are excited to see what the future holds for this innovative initiative.

Keys: SENSE project, haptic device, sensory exploration, nature, web application, textures, fur, scales, tree barks, bees, school kids, think-aloud protocol, data analysis, hands-on, user-friendly, education, innovation.

Team: Shuang Ao, Stefan Rueger, Nirwan Sharma, Advaith Siddharthan

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Publications

Publications | Visit External Site for Details  
Publications | Visit External Site for Details  

Islam, R., Gooch, D., Sampath, S., Karlakki, S., Jones, T., Sayers, C. and Price, B. (2023) SliderĀ®-A Novel Device For Remote Tracking Of Physiotherapy Exercises In Patients With Osteoarthritis Of The Knee: An Early Report, EFORT Annual Congress 2023, Vienna, Austria

Publications | Visit External Site for Details Publications | doi 

Islam, R., Gooch, D., Karlakki, S. and Price, B. (2023) SliderĀ® device for prehabilitation of total knee replacement surgery: usability study, JMIR Formative Research, pp. (Early access)

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Dr. Siān Lindley
Microsoft Research Cambridge

Actions and their Consequences: Implicit Interactions with Machine Learned Knowledge Bases

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