Deren's Tangible Studio Project

Project Name: Rebbelib Reconstructed
Maker: Deren Guler

Abstract:

Rebbelib Reconstructed is a robotic grid based on an ancient stick chart used by Micronesian sailors to show sailing paths. I hope to develop algorithms that abstract tangible and intangible data into analogous shapes that depict complex relationships in a simple tangible object. I would like to be able to represent a range of concepts such as the passage of different traditions throughout time versus the emergence of new technology. Using shapes within a grid could serve as a novel data visualization technique for not only sailors, but for students, designers, and professionals in many other disciplines.




Description/Timeline:

The grid lines can change angle and curve and are controlled by servomotors. This projects aims to create a data visualization method to represent abstract information within the constraints of a grid. Grids are very common in maps. It has been found that they are a very effective way of illustrating concepts such as time, distance, height, and orientation. The shape of an object, i.e. the amount of corners it has, and how curved the sides are, can also be interpreted to convey different relationships.

I have built a prototype and a simulation of the project and done research on how to limit the augmentation of the grid. The prototype only used 6 motors and I have redesigned it to include 16 motors using an IC that allows for more PWM channels. I am working on integrating the library for this with the library for Pachube, which send remote sensor feeds to the Arduino. I would also like to make it wireless and use XBee, but this is not necessary.

This week I plan to finish modeling the base/frame of the structure and put together the final circuit. I hope to spend the next two weeks tweaking the design and testing different algorithms in the code to see what will work best. I am also going to design a user interface for changing the sensor readings. By the final presentation I want to have an 8 x 8 grid that can respond to a range of sensor inputs and display different data in an easily comprehensible method.

Tangible Studio Exhibition :: Tobias

For the tangible studio exhibition I expect to have the following
working:

Title: Helping people improve their ergonomics through active
feedback devices.

Many people work for long hours at a workstation. This leads to pain
and long-term injury due to poor posture and ergonomics.

The Active Health Series is a product line that helps people help
themselves by providing feedback to the users instead of just masking
the problem, as done by other solutions.

The product line consists of:

The Active Health Bracelet is for people working long hours at a
workstation who want to prevent or heal CTS. It provides light and
vibration feedback based on the position of the user's hands, unlike
other products on the market, which are passive. The bracelet helps
people learn when their hand position is not in a correct, healty
position and thereby avoids the pain which inevitably follows a
chronically bad hand position.

The Active Health Suspenders and Active Health Shirt are for people
who want to correct their bad posture. It provides active feedback
through vibration based on the users posture, unlike most other
products on the market.

The Active Health Break-O-Meter is for people working in front of
computers all day who want to improve their productivity and
health. The Active Health Break-O-Meter is a personal table device
that detects how long you have been sitting in the same position, and
notifies you when it is time to take a short break. While there are
software-based solutions, the break-o-meter is the only physical
device of this kind.

Milestones:

November 8 - 10 :: The Active Health Bracelet:
I will complete it in this week. This involves making better use of
the BlinkMs and optimizing the code. I do not plan to hide the
hardware unless you think that this is a good idea.

November 15 - 22 :: The Active Health Suspenders:
I will receive a pair of suspenders on Wednesday, and hopefully make a
quick prototype test before Friday Nov 11. If the test turns out well,
I will build the next version of the prototype from November 15th to
the 22nd.


Nov. 22 - Dec 1 :: The Active Health Shirt:
I bought a tight shirt, and I will try to attach my homemade flex
sensors to it. I hope to have this project finished November 30.

December 1 - 7 :: Poster, videos, unfinished stuff etc.

SENSEable Shoes (proposal)

Abstract

SENSEable Shoes can understand human behaviors and thus provide a tangible wearable interface for interaction. By getting the values from twelve pressure sensors under shoe-pads in shoes (left foot and right foot), the algorithm can identify distinct feet gestures and predict the status of human behaviors related to shoes (such as changing the center of gravity of feet soles to the right/left/front/back, standing with two legs or one legs, sitting straight, sitting and leaning back, sitting and moving feet, shaking legs, walking, running, going upstairs or downstairs, jumping).

Problem

This is a Physiological Data Modeling problem whose purpose is to classify the person's behavior patterns based on the sensor measurements. In order to customize according to different person’s behavior patterns, the software will use python 2.7 with SciPy, Numpy, and Matplotlib API to implement a machine learning algorithm.

Midterm Milestone

The algorithm predicts static statuses of human behaviors related to shoes (standing with two legs or one legs, sitting straight, sitting and leaning back, changing the center of gravity of feet soles to the right/left/front/back).

Final Milestone

The algorithm predicts dynamic statuses of human behaviors related to shoes (sitting and moving feet, shaking legs, walking, running, going upstairs or downstairs, jumping). A tangible user interface will be constructed to interact with the shoes. (Sorry I haven’t come up with an idea about the interface.)

References

Chen, M., & Huang, B. (2008). Intelligent shoes for abnormal gait detection. 2008 IEEE International Conference on Robotics and Automation, 2019-2024. Ieee. doi:10.1109/ROBOT.2008.4543503