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Watch-ya-doin

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Watch-ya-doin is an innovative experienced based sampling framework for longitudinal data collection and analysis. Our system consists of a smartwatch and an android device working unobtrusively to track data. Our goal is to train on and recognize a specific activity over time. We use a simple wrist-worn accelerometer to predict eating behavior and other activities. These are inexpensive to deploy and easy to maintain, since battery life is a whole week using our application.
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     Our primary application area is AT abandonment. About 700,000 people in the United States have an upper limb amputation, and about 6.8 million face fine motor and/or arm dexterity limitations[1]. Assistive technology (AT), ranging from myo-electric prosthetics to passive prosthetics to a variety of orthotics can help in the rehabilitation and improve independence and ability to perform everyday tasks. Yet AT is not used to its full potential, with abandonment rates ranging from 23% to 90% for prosthetics users, and high abandonment of orthotics as well. Given the cost of these devices, this is an enormous waste of a significant financial investment in developing, fabricating, and providing the device, as well as potentially leading to frustration, insufficient rehabilitation, increased risk of limb-loss associated co-morbidities, and overall a reduced quality of life for the recipient.
       To address this, we need objective and accurate information about AT use. Current data is limited primarily to questionnaires, or skill testing during office visits. Apart from being limited by subjectivity and evaluator bias, survey tools are also not appropriate to estimate quality of use. A patient may – more or less accurately – report his or her AT use for a certain number of hours a day, but this does not indicate which tasks it was used for, which makes it difficult to evaluate how appropriate or helpful they were. In addition, neither reported use time nor skill testing can be sufficiently used to predict abandonment once AT is deployed.

      Our next steps include generalizing our approach to AT (such as upper limb prosthetics), and expanding it to include a wider variety of tracked activities. In addition, we will develop a longitudinal data set that includes examples of abandonment. This will allow the creation algorithms that can characterize the type and quality of use over the lifecycle of AT and predict abandonment.

[1] U.S. Census 2001

Printable Adaptations

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Reprise: A Design Tool for Specifying, Generating, and Customizing 3D Printable Adaptations on Everyday Objects

Reprise is a tool for creating custom adaptive 3D printable designs for making it easier to manipulate everything from tools to zipper pulls. Reprise’s library is based on a survey of about 3,000 assistive technology and life hacks drawn from textbooks on the topic as well as Thingiverse. Using Reprise, it is possible to specify a type of action (such as grasp or pull), indicate the direction of action on a 3D model of the object being adapted, parameterize the action in a simple GUI, specify an attachment method, and produce a 3D model that is ready to print.

Xiang ‘Anthony’ Chen, Jeeeun Kim, Jennifer Mankoff, Tovi Grossman, Stelian Coros, Scott Hudson (2016). Reprise: A Design Tool for Specifying, Generating, and Customizing 3D Printable Adaptations on Everyday Objects. Proceedings of the 29th Annual ACM Symposium on User Interface Software and Technology (UIST 2016) (pdf)

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A Knitting Machine Compiler

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A teddy bear wearing a knit hat, scarf (with pocket) and sweaterAlthough industrial knitting machines can automatically produce a wide range of garments, they are programmed through onerous means such as pixel level image manipulation. This limits the potential for automation of knitted object design, re-use of object components, and narrows the audience able to design for these machines. Our contribution is a visual design interface for specifying objects in terms of tubes and sheets and a compiler that can convert such an object into knittable machine instructions which handle knotty issues such as transfer planning (among needles) correctly. We demonstrate the range of objects our approach supports by example.

A Compiler for 3D Machine Knitting (SIGGRAPH 2016) Jim McCann, Lea Albaugh,
Vidya Narayanan, April Grow, Wojciech Matusik, Jennifer Mankoff, Jessica Hodgins

RapID — interactive RFID

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RapID – A framework for fabricating low-latency interactive objects with RFID tags

RFID tags can be used to add inexpensive, wireless, batteryless sensing to objects. However, quickly and accurately estimating the state of an RFID tag is difficult. In this work, we show how to achieve low-latency manipulation and movement sensing with off-the-shelf RFID tags and readers. Our approach couples a probabilistic filtering layer with a monte- carlo-sampling-based interaction layer, preserving uncertainty in tag reads until they can be resolved in the context of interactions. This allows designers’ code to reason about inputs at a high level. We demonstrate the effectiveness of our approach with a number of interactive objects, along with a library of components that can be combined to make new designs.

bestRapID: A Framework for Fabricating Low-Latency Interactive Objects with RFID Tags (CHI 2016, Page 5897) Andrew Spielberg, Alanson Sample, Scott E. Hudson, Jennifer Mankoff, James McCann

mixer-use quiz-use tic-tac-toe-play
pong-use pong-build tic-tac-toe-sketchup

Modeling Human Routines

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Modeling and Understanding Human Routine Behavior

Human routines are blueprints of behavior, which allow people to accomplish their purposeful repetitive tasks and activities. People express their routines through actions that they perform in the particular situations that triggered those actions. An ability to model routines and understand the situations in which they are likely to occur could allow technology to help people improve their bad habits, inexpert behavior, and other suboptimal routines. In this project we explore generalizable routine modeling approaches that encode patterns of routine behavior in ways that allow systems, such as smart agents, to classify, predict, and reason about human actions under the inherent uncertainty present in human behavior. Such technologies can have a positive effect on society by making people healthier, safer, and more efficient in their routine tasks.

Routines_Viz_Tool

Modeling and Understanding Human Routine Behavior
Nikola Banovic, Tofi Buzali, Fanny Chevalier, Jennifer Mankoff, and Anind K. Dey
In Proceedings of the 2016 ACM annual conference on Human Factors in Computing Systems(CHI ’16). ACM, New York, NY, USA.
Honorable Mention Award

Dynamic question ordering

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In recent years, surveys have been shifting online, offering the possibility for adaptive questions, where later questions depend on responses to earlier questions. We present a general framework for dynamically ordering questions, based on previous responses, to engage respondents, improving survey completion and imputation of unknown items. Our work considers two scenarios for data collection from survey-takers. In the first, we want to maximize survey completion (and the quality of necessary imputations) and so we focus on ordering questions to engage the respondent and collect hopefully all the information we seek, or at least the information that most characterizes the respondent so imputed values will be accurate. In the second scenario, our goal is to give the respondent a personalized prediction, based on information they provide. Since it is possible to give a reasonable prediction with only a subset of questions, we are not concerned with motivating the user to answer all questions. Instead, we want to order questions so that the user provides information that most reduces the uncertainty of our prediction, while not being too burdensome to answer.

Publications
Kirstin Early, Stephen E. Fienberg, Jennifer Mankoff. (2016). Test time feature ordering with FOCUS: Interactive predictions with minimal user burden. In Proceedings of 2016 ACM Conference on Pervasive and Ubiquitous Computing. Honorable Mention: Top 5% of submissions. Talk slides.

3D printed attachments

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Encore: 3D printed attachments

What happens when you want to 3D print something that must interact with the real world? The Encore project makes it possible to 3D print objects that must attach to things in the real world. Encore provides an interface that, given an imported object and a chosen attachment method, visualizes metrics relating the goodness of the attachment. In addition, once an attachment type and location is chosen, Encore helps to produce the necessary support structure for attachment. Encore supports three main types of attachment: print-over, print-to-affix, and print-through.

Print-Over

Print-over attachments are printed directly on the existing object. This works well if the object is flat enough that the print head won’t encounter obstacles as it moves, and the object is made of a material that the printed material will easily adhere to. Encore helps by finding a rotation of the existing object that minimizes obstacles, and generating support material to hold the existing object in place.

Printing a magnet holder over a Teddy bear toy.
 
Left: printing an LED casing on a battery to make a simple torch; right: printing a handle to an espresso cup.
 

Print-to-Affix

An alternative that is useful when the existing object does not fit on the print bed is print-to-affix. In this approach, the attachment is designed to fit snugly against the existing object. It may be glued in place, or can include holes for a strap, such as a zip tie.

Left: printing a structure to make a glue gun stand; right: printing a reusable four-pack holder.
 

Print-Through

Finally, sometimes the attachment should be interlocked more loosely with the existing object. In this case, the process is to begin printing and stop the print partway through so that the existing object can be inserted. Encore can compute when this stopping point should be (and
whether it is possible)

A name tag printed through a pair of scissors
 
A bracelet printed through a charm
 

Encore the Design Tool

Encore is implemented in WebGL. It supports importation of an existing object, selection of an attachment, and then lets the user click to indicate where the attachment will go. Given this information, it uses geometric analysis to compute metrics for goodness of attachment, such as attachability and strength. Encore visualizes them using a heat map so that the user can adjust the attachment point.


Encore visualizes which parts of a wrench are more attachable when printing over a handle.

More Examples


Using print-to-affix to make a trophy from an egg holder
 

Using print-over to make a minion keychain
 

Using print-over to add a hanger to a screwdriver handle
 

Using print-through to make a key ring.
 

Using print-to-affix to make a battery case
 
Xiang ‘Anthony’ Chen, Stelian Coros, Jennifer Mankoff, Scott Hudson (2015). Encore: 3D Printed Augmentation of Everyday Objects with Printed-Over, Affixed and Interlocked Attachments. Proceedings of the 28th Annual ACM Symposium on User Interface Software and Technology (UIST 2015)

Helping Hands

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Prosthetic limbs and assistive technology (AT) require customization and modification over time to effectively meet the needs of end users. Yet, this process is typically costly and, as a result, abandonment rates are very high. Rapid prototyping technologies such as 3D printing have begun to alleviate this issue by making it possible to inexpensively, and iteratively create general AT designs and prosthetics. However for effective use, technology must be applied using design methods that support physical rapid prototyping and can accommodate the unique needs of a specific user. While most research has focused on the tools for creating fitted assistive devices, we focus on the requirements of a design process that engages the user and designer in the rapid iterative prototyping of prosthetic devices.

We present a case study of three participants with upper-limb amputations working with researchers to design prosthetic devices for specific tasks. Kevin wanted to play the cello, Ellen wanted to ride a hand-cycle (a bicycle for people with lower limb mobility impairments), and Bret wanted to use a table knife. Our goal was to identify requirements for a design process that can engage the assistive technology user in rapidly prototyping assistive devices that fill needs not easily met by traditional assistive technology. Our study made use of 3D printing and other playful and practical prototyping materials. We discuss materials that support on-the-spot design and iteration, dimensions along which in-person iteration is most important (such as length and angle) and the value of a supportive social network for users who prototype their own assistive technology. From these findings we argue for the importance of extensions in supporting modularity, community engagement, and relatable prototyping materials in the iterative design of prosthetics

Prosthetic limbs and assistive technology (AT) require customization and modification over time to effectively meet the needs of end users. Yet, this process is typically costly and, as a result, abandonment rates are very high. Rapid prototyping technologies such as 3D printing have begun to alleviate this issue by making it possible to inexpensively, and iteratively create general AT designs and prosthetics. However for effective use, technology must be applied using design methods that support physical rapid prototyping and can accommodate the unique needs of a specific user. While most research has focused on the tools for creating fitted assistive devices, we focus on the requirements of a design process that engages the user and designer in the rapid iterative prototyping of prosthetic devices.

We present a case study of three participants with upper-limb amputations working with researchers to design prosthetic devices for specific tasks. Kevin wanted to play the cello, Ellen wanted to ride a hand-cycle (a bicycle for people with lower limb mobility impairments), and Bret wanted to use a table knife. Our goal was to identify requirements for a design process that can engage the assistive technology user in rapidly prototyping assistive devices that fill needs not easily met by traditional assistive technology. Our study made use of 3D printing and other playful and practical prototyping materials. We discuss materials that support on-the-spot design and iteration, dimensions along which in-person iteration is most important (such as length and angle) and the value of a supportive social network for users who prototype their own assistive technology. From these findings we argue for the importance of extensions in supporting modularity, community engagement, and relatable prototyping materials in the iterative design of prosthetics

Photos

The length of his arm, significantly impacted Kevin’s ability to play the cello. During the prototyping process he was able to test a variety of lengths by adding on layers of Lego to his prototyping prosthetic.
Kevin enjoys his latest cello bow holder so much that, according to his mother, she’s not allowed to touch or adjust it in case it gets messed up.
“Life changing technology can come in many forms; it can come in the form of Styrofoam and pipe cleaners,” Said one participant while working on adjusting the angle of her prosthetic to maximize her comfort while gripping a hand-cycle.
This 3D printed prosthetic demonstrates the value of creating prosthetics for a very specific task (in this case control of a hand-bike), and the importance of manipulating factors such as angle.
Brett M. Fadgen MSN, CRNA. is a practicing Nurse Anesthetist with an amputation below his left elbow. He has customized his profesional grade prosthetics to help him perform nursing tasks.
Despite having a wide variety of professionaly designed prosthetic devices, Bret never found a good solution for using a common table knife. Using 3D scanning technology and modeling clay we were able to design a custom grip that could stabilize the knife in his myoelectric hand.

Project Files

https://www.thingiverse.com/thing:2365703

Project Publications

Helping Hands: Requirements for a Prototyping Methodology for Upper-limb Prosthetics Users

Reference:

Megan Kelly Hofmann, Jeffery Harris, Scott E Hudson, Jennifer Mankoff. 2016.Helping Hands: Requirements for a Prototyping Methodology for Upper-limb Prosthetics Users. InProceedings of the 34th Annual ACM Conference on Human Factors in Computing Systems (CHI ’16). ACM, New York, NY, USA, 525-534.

Making Connections: Modular 3D Printing for Designing Assistive Attachments to Prosthetic Devices

Reference:

Megan Kelly Hofmann. 2015. Making Connections: Modular 3D Printing for Designing Assistive Attachments to Prosthetic Devices. In Proceedings of the 17th International ACM SIGACCESS Conference on Computers & Accessibility (ASSETS ’15). ACM, New York, NY, USA, 353-354. DOI=http://dx.doi.org/10.1145/2700648.2811323

Supporting Navigation in the Wild for the Blind

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uncovering_thumbnailSighted individuals often develop significant knowledge about their environment through what they can visually observe. In contrast, individuals who are visually impaired mostly acquire such knowledge about their environment through information that is explicitly related to them. Our work examines the practices that visually impaired individuals use to learn about their environments and the associated challenges. In the first of our two studies, we uncover four types of information needed to master and navigate the environment. We detail how individuals’ context impacts their ability to learn this information, and outline requirements for independent spatial learning. In a second study, we explore how individuals learn about places and activities in their environment. Our findings show that users not only learn information to satisfy their immediate needs, but also to enable future opportunities – something existing technologies do not fully support. From these findings, we discuss future research and design opportunities to assist the visually impaired in independent spatial learning.

Uncovering information needs for independent spatial learning for users who are visually impaired. Nikola Banovic, Rachel L. Franz, Khai N. Truong, Jennifer Mankoff, and Anind K. DeyIn Proceedings of the 15th international ACM SIGACCESS conference on Computers and accessibility (ASSETS ’13). ACM, New York, NY, USA, Article 24, 8 pages. (pdf)

Layered Fabric Printing

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A Layered Fabric 3D Printer for Soft Interactive Objects. Huaishu Peng, Jennifer Mankoff, Scott E. Hudson, James McCann. CHI ’15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 2015.

In work done collaboratively with Disney Research and led by Disney Intern Huaishu Peng (of Cornell), we have begun to explore alternative material options for fabrication. Unlike traditional 3D printing, which uses hard plastic, this project made use of cloth (in the video shown above, felt). In addition to its aesthetic properties, fabric is deformable, and the degree of deformability can be controlled. Our printer, which works by gluing layers of laser-cut fabric to each other also allows for dual material printing, meaning that layers of conductive fabric can be inserted. This allows fabric objects to also easily support embedded electronics. This work has been in the news recently, and was featured at Adafruit; Futurity; Gizmodo; Geek.com and TechCrunch, among others.