ExoArm: An Arduino-powered assistive exoskeleton arm

Whether to enhance one’s abilities or to compensate for a loss of strength due to a variety of reasons, the idea of a robotic exoskeleton is an exciting prospect. As seen here, Kristjan Berce, not content to let well-funded labs have all the fun, decided to make his own prototype assistive arm using simple hand tools to manufacture a bracing system over his left arm.

Control for the device, which is called “ExoArm,” is accomplished with an Arduino Uno that powers a windshield wiper motor via a driver board. As set up now, it extends via sensor input, and contracts with the push of a button.

Though it can be seen helping him lift a bicycle at the end of both of his videos, figuring out how to balance any load on the system with his actual muscle’s input is a challenge he’s still working on, but hopes to solve this issue using a strain gauge.

Total cost of ExoArm? $ 100. You can follow along with Berce’s progress on the project’s log here.

Arduino Blog

MIT & Watson: hacking assistive technology for #AccessibleOlli

It’s a frigid Saturday morning and I’m on my way to attend the Assistive Technology Hackathon at Massachusetts Institute of Technology in Cambridge. I knew that one of the hack challenges presented by IBM Research and IBM technology partner Local Motors was designed to address difficulties that the blind and visually impaired face on urban transportation, so I took off my glasses just before hopping onto the Red Line of Boston’s subway system. It was immediately apparent that this challenge would address far more than finding a seat as a matter of convenience.

285 million reasons why assistive technology is important

For the more than 285 million global citizens with visual impairment, enhanced public transportation provides a huge step forward for both personal and economic independence. As the hackathon project team learned, having the capability to find an empty seat on a bus, or train is not only an issue of personal safety, but also empowers individuals with physical limitations to get to work, shop for food, and conduct day to day life tasks.

#AccessibleOlli at MIT : scouting for new accessibility apps

Upon arriving at MIT’s BeaverWorks Lab, I checked in with a team of student coders, mechanical engineers, an occupational therapist, and the team clients – Erich Manser from IBM Research and Gina O’Connell from Local Motors.

Gina was attending with IBM to scout out prospective future applications for Olli, billed as the world’s first cognitive self-driving shuttle. The students had been busy building an Android-based app that used Bluetooth and overhead cameras that could be mounted in a city bus, or in a smaller specially equipped Olli shuttle, to identify available seats and provide verbal navigation to the user based on their geospatial coordinates when coming on board. A key element of the app was empathic design, with the entirety of the device screen acting as one big function key; this single point of app navigation enabled the identification of available seats with a just one touch.

The solution built by the students could also be extended.to many forms of public and private transportation systems as well as other fixed seat environments like MITs lecture halls.

Flawless functionality: the app was up to the task

The application functioned flawlessly in the lab, but is public transport ready to invest widely in assistive solutions like the seat-finder app?  As it turns out – it seems the answer is yes. Gina shared that her company is looking at accessibility from four different perspectives – visual, audio, cognitive and mobility–in an effort to address the needs of an estimated 15 percent of the world’s population who experience some form of disability.

By incorporating IBM Watson APIs like text-to-speech and image recognition, additional assistive on board services for self-driving Olli could include machine learning for seat selection and familiar destinations by rider, sign language recognition, and schedule arrival/departure notifications delivered to users’ personal mobile devices.

A diagram of Olli, the autonomous cognitive vehicle from Local Motors powered by Watson IoT

Figure 1: Olli

Crowd-sourcing innovative ideas

Throughout 2017, Local Motors will be teaming with IBM, the Consumer Technology Association, the American Association of Retired Persons (AARP) and a number of other associations and municipalities to explore and enhance transportation for the aged population and those with physical or cognitive limitations. The extended group will also be working with student teams internationally, like those at MIT, crafting and submitting accessible technologies that bridge generation gaps.   Currently, there is a Local Motors Olli vehicle resident in the IBM Watson IoT global headquarters in Munich, Germany, where researchers from around the world can contribute to its learning and association with assistive technology.

The potential?

New collaboration between technology partners and large associations serving the needs of aging and disabled individuals represents a unique opportunity to better meet the needs of the entire community – as well as a multi-billion dollar opportunity. By leveraging the power of IoT and cognitive computing, in effect, we are putting new knowledge at the fingertips of the entire ecosystem – creating a limitless set of collaborative ideas which could potentially improve the experiences for aging and disabled individuals, while encouraging different players to enter the market.

Hats off to the MIT student hack team

Hats off to student hack team at MIT and their seat finding app : Sharon Hershenson, Dhruvika Sahni, Ayush Sharma, Yao Tong, Xin Wen and Fangzhou Xia. Watch for more news on student hacks and workshops supported by IBM Research, IBM Watson IoT and Local Motors.

Want to get involved? Follow: #AccessibleOlli

Please participate and share your ideas with the hashtag #AccessbleOlli. For more information, please visit ibm.com/able/

Checkout the Accessible Olli video.

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