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On-body input interfaces that can be used accurately without visual attention could have a wide range of applications where vision is needed for a primary task: emergency responders, pilots, astronauts, and people with vision impairments could benefit by making interfaces accessible. This paper describes a between-participant study (104 participants) to determine how well users can locate e-textile interface discrete target touch points on the forearm without visual attention. We examine whether the addition of active touch embroidery and passive touch nubs (metal snaps with vibro-tactile stimulation) helps in locating input touch points accurately. We found that touch points towards the middle of the interface on the forearm were more difficult to touch accurately than at the ends. We also found that the addition of vibro-tactile stimulation aids in the accuracy of touch interactions by over 9% on average, and by almost 17% in the middle of the interface.

Age-related changes in functional ability, particularly among people aging with long-term disabilities, can impact safe performance of toilet and bathtub transfers and severely limit their ability to successfully age-in-place. The SmartBathroom is a state-of-the-art bathroom laboratory that features mechanically adjustable features and an array of sensors that can measure walking performance, location of feet and hands, and forces applied to the bathroom surfaces and fixtures. To complement the SmartToilet system, TechSAge recently developed the SmartBathing Transfer Testbed prototype that will enable us to study how different bathing environment configurations can impact transfer performance. The testbed consists of a height adjustable tub wall and three-wall, height and angle adjustable grab bars with integrated sensors to measure hand location and grip and load forces. This session will describe the SmartBathing Testbed and present results of studies with individuals both with and without ambulatory impairments performing simulated transfers within the testbed.

A reliable fall detection device is crucial to minimize long-term consequences of falls among wheelchair users. This study examines the sensitivity of Apple Watch to detect intentional falls from a wheelchair. Twenty-five able bodied (age: 21.9 ± 2.5 years) participated in a protocol in which they intentionally fell out of a wheelchair in a laboratory setting. Each participant wore an Apple Watch Series 5 and performed 3 falls in the forward, right and left sideways, and backward directions onto a crash pad totaling 12 falls each. The Apple Watch was manually checked after each fall to determine if the device registered a fall. From 300 fall trials captured, the Apple Watch detected 14 falls showing a sensitivity of 4.7%, a false negative rate of 95.3%. Logistic regression showed that participant's height, impact force, lower limb functioning, and fall direction are parameters that may influence the ability of the Apple Watch to detect falls from a wheelchair. The Apple Watch fall detection feature presented with a very poor sensitivity to detect intentional falls from a wheelchair among able bodied young adults. Due to the high incidence and consequences of falls, a reliable fall detection device specific for wheelchair users is warranted.

Background Falls are a concern for older adults who use wheelchairs and scooters. Many wheelchair and scooter users require assistance to recover from a fall and often lie on the ground waiting for assistance for 10 min or more. An automated fall detection device may facilitate communication with care partners and expedite recovery; however, there is limited research on the specifications and features of an automated fall detection device preferred by older adults who use wheelchair and scooter. Objective To examine the desired specifications, perceived ease of use and perceived usefulness of an automated fall detection device desired by older adults who use a wheelchair or scooter through semi-structured interviews. Methods Fifteen full-time wheelchair and scooter users (9 females; age: 68 ± 5 years) were interviewed from July to November 2020. Interviews were transcribed, coded, and analyzed. Results Preferred features include wireless charging, a watch form, ability to change the individual who is contacted in the event of a fall, and the ability to disable a notification in the event of a false alarm. Participants felt that an automated fall detection device would be useful and easy to use. Conclusions Older adults who use a wheelchair or scooter indicated the need for an automated fall detection device to facilitate recovery from a fall. Participants reported challenges with previous fall detection devices and the need for specific design requirements to facilitate ongoing use. Participants’ insights inform the design of a fall detection device to maximize usability and prevent technology abandonment.

Haptic technology can be used as a tool for learning. Can even the haptic elements in a smartwatch teach a new skill? Here we present a case of using a smartwatch for passive tactile learning. We use the Sony Smartwatch 3 to teach users Morse code while they wear the watch but focus on unrelated tasks. An initial hypothesis forecasted that the stimulation from the smartwatch, typically used for message alerts, would be too subtle to enable haptic learning; however, we find significant improvements in six participants using the technique. Furthermore, we expose participants to two different durations of stimulation and find different results.

Systems that recognize silent speech can enable fast, hands-free communication. Two prototypes let users control Google Glass with tongue movements and jaw gestures, requiring no additional equipment except a tongue-mounted magnet or consumer earphones augmented with embedded proximity sensors.

Previous research has established the connection between the way in which children interact with objects and the potential early identification of children with autism. Those findings motivate our own work to develop "smart toys," objects embedded with wireless sensors that are safe and enjoyable for very small children, that allow detailed interaction data to be easily recorded. These sensor-enabled toys provide opportunities for autism research by reducing the effort required to collect and analyze a child's interactions with objects. In the future, such toys may be a useful part of clinical and in-home assessment tools. In this paper, we discuss the design of a collection of smart toys that can be used to automatically characterize the way in which a child is playing. We use statistical models to provide objective, quantitative measures of object play interactions. We also developed a tool to view rich forms of annotated play data for later analysis. We report the results of recognition experiments on more than fifty play sessions conducted with adults and children as well as discuss the opportunities for using this approach to support video annotation and other applications.

WOS: 000271672600011 PubMed: 19648898 Purpose A new perimetry method is described to evaluate central vision under multiple hue, illumination, and contrast conditions; results are described for normal individuals using high-contrast targets. Methods For 70 normal eyes of individuals with varying age, the ETDRS chart acuity was determined as well as discriminated target perimetry using high-contrast targets presented for 250 ms at locations up to 10 degrees eccentricity. Retesting was performed to evaluate for learning and repeatability for the thresholded acuity at each eccentricity. Results The ETDRS acuity averaged 1.15 +/- 0.37 arc min minimum angle of resolution (MAR) with best correction (20/23 equivalence). At fixation, the thresholded acuity for high-contrast targets paralleled the ETDRS acuity and averaged 1.75 +/- 0.85 arc min MAR (20/35 equivalence), and declined with increasing eccentricity in a linear fashion to 5.81 +/- 3.97 arc min (20/116 equivalent) at 10 degrees eccentricity. Linear regression showed Vmar = 1.74 vertical bar 0.330 * eccentricity in degrees (R-2 = 0.966, P < 0.0001). Testing time required similar to 8-10 min per eye. Repeated testing showed only minimal learning experience at the most peripheral locations. The test-retest 95% confidence limits of difference measured 1.12 arc mins MAR at fixation (64% of the mean) and remained approximately the same proportion to the mean thresholded acuity outwards to 10 degrees eccentricity. Conclusion The methodology seems rapid and reliable for measuring discriminatory visual function of optotype targets throughout the central 20 degrees diameter visual field. Eye (2009) 23, 2082-2089; doi:10.1038/eye.2009.177; published online 17 July 2009

WOS: 000263321000035 PubMed: 19039333 Purpose This pilot study was undertaken to examine the relationships between clinical measures of visual function and anatomic changes occurring in the eyes treated with bevacizumab for choroidal neovascularization (CNV) due to age-related macular degeneration (AMD). Methods A retrospective review was conducted for 50 eyes that had been treated with at least three injections of bevicizumab for CNV due to AMD, and followed for at least 6 months. Vision outcomes included best-corrected ETDRS chart acuity, scored by best-line read (ETDRS line) and by total letters read (ETDRS letter), and two measures obtained from central acuity perimetry with 98% Michelson contrast targets, the best acuity within 6 degrees of fixation (BA6 degrees), and global macular acuity (GMA), representing a weighted average of the acuities thresholded at all intercepts within a 10 degrees radius of fixation. Assessment of anatomic outcomes included fibrosis, atrophy, and subretinal hemorrhage grading on fundus photography, CNV size, pigment epithelial detachment (PED) size and grading of CNV leakage on fluorescein angiography, and central retinal PED, and subretinal fluid (SRF) thickness on optical coherence tomography. Results Logistic regression analysis showed an association between the vision outcomes of EDTRS letter and BA6 degrees with the change in SRF thickness (R-2: 0.47 and 0.35, respectively). The outcome of the vision measurement of GMA was associated with the change in SRF thickness, in CNV thickness, and in CNV fibrosis grade (R-2: 0.34). No association was noted between the outcomes of ETDRS line with the change in any anatomic outcomes. Conclusion Acuity perimetry outcomes in this study seemed to offer improved understanding of the relationship between the vision outcomes and the measured anatomic changes. It seemed that neither ocular coherence tomography nor fluorescein angiography alone offered sufficient morphologic markers for prediction of functional outcomes. TUBITAKTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) This study was supported by TUBITAK.

The human ear seems to be a rigid anatomical part with no apparent activity, yet many facial and body activity can be measured from it. Research apparatuses and commercial products have demonstrated the capability of monitoring hart rate, tongue activities, jaw motion and eye blinking from the ear. In this paper we describe the design and the implementation of the Outer Ear Interface (OEI) which utilizes a set of infrared proximity sensors to measure the deformation in the ear canal caused by the lower jaw movement. OEI has been used in different applications that requires tracking of jaw activity which includes silent speech recognition, jaw gesture detection and food intake monitoring.

Wearable technology projects sometimes present complex problems, which are hard to solve through computer science solutions alone. Our interdisciplinary team met such a problem in the form of near infrared sensor noise due to fabric interference. We met the challenge through software/hardware solutions, but also strategic fabric selection and soft-good construction. This case study shows how incorporating everyone's expertise on an interdisciplinary team can afford solutions, which better accomplish the goals of a project than individual disciplines could alone.

Purpose: The CVA is an interactive, automated computer device that rapidly thresholds central acuity under conditions mimicking customary photopic and mesopic activities. In sequence, the CVA may test up to 6 environments, in this series under 3 mesopic environments (98%, 50% MC against 1.6 cd/m2 background, 25% MC against 5 cd/m2), then 3 glare environments (98%, 10% and 8% MC, against 200 cd/m2). This report compares the CVA thresholded acuity with that measured with letter charts, as well as with C-Quant derived glare testing and patient responses to the Activities of Daily Vision Scale (ADVS) in eyes with nuclear cataract. Methods: In 33 eyes with nuclear cataract compared with 69 emmetropic eyes without lens opacity, best refracted acuity was measured under CVA modules and with ETDRS charts presenting similar contrast and luminance. Both groups were also tested with 15% MC charts placed outdoors with sun overhead and with sun at 15° off-axis and compared with the CVA acuty at 10% MC and 8% MC thresholded in a darkened room. In 22 of the eyes with nuclear cataract, C-Quant analysis of straylight glare was also performed along with the ADVS. Results: Acuities thresholded with CVA modules demonstrated high Pearson correlation coefficients, and Bland and Altman statistical similarity with the acuities measured from similar contrast charts. The acuities measured with CVA glare modules correlated significantly with charts placed in sun glare and with C-Quant measurements of straylight. Significant correlations were noted between CVA acuities and near vision as well as distance driving tasks. Conclusions: The CVA demonstrates the ability to accurately threshold the acuity of eyes with nuclear cataract compared with chart acuity under conditions of contrast, luminance and fixation times simulating normal photopic and mesopic activities and to provide the physician with glare evaluation and ability to function under multiple types of activities.

Purpose: The Central Vision Analyzer (CVA) is an interactive, automated computer device that rapidly thresholds central acuity under conditions mimicking customary photopic and mesopic activities. In sequence, the CVA may test up to 6 environments, and in this series was used to test 3 mesopic environments (98% and 50% MC against 1.6 cd/m2 background, 25% MC against 5 cd/m2), then 3 glare environments (98%, 10% and 8% MC, against 200 cd/m2 background). This report compares the CVA thresholded acuity with that measured utilizing standard letter acuity charts. Methods: In 481 normal eyes acuity was measured with best spectacle and contact lens refraction using both CVA and 0.1 logMAR ETDRS charts presenting similar contrast and luminance. In addition for 162 emmetropic, eyes, acuity was tested with a 15% MC chart placed outdoors with sun overhead and with sun at 15° off-axis and compared with the CVA thresholded acuity at 10% and 8% MC presented in a darkened room. Results: All CVA modules demonstrated high Pearson correlation coefficients (r=0.51 to r=0.94, p

Grid laser is recognized as an extremely effective treatment of diabetic macular edema, although it causes significant chorioretinal damage when applied and scars that expand with time. The purpose of this study is to compare the effects of two methods of grid laser photocoagulation for diabetic macular edema on high-contrast target discrimination in the central visual field. Grid laser photocoagulation with the Early Treatment Diabetic Retinopathy Study intensity burns has previously been shown to cause full retinal thickness burns. In this study, it produced severe destruction of paraxial vision, most marked at 2 degrees to 10 degrees from fixation. Grid laser using threshold-level burns, in contrast, appeared to produce some improvement in thresholded high-contrast vision at eccentricities from 2 degrees to 3 degrees outward, but failed to normalize visual parameters at these intercepts or at intercepts closer to fixation. Therefore, the recommendations are made (1) to use screening modalities other than biomicroscopic perception of retinal swelling to define earlier opportunities for intervention in the diabetic maculopathic process and (2) to use threshold or sub-threshold methods of laser grid photocoagulation for treating leakage and/or edema.

Research in dolphin cognition and communication in the wild is still a challenging task for marine biologists. Most problems arise from the uncontrolled nature of field studies and the challenges of building suitable underwater research equipment. We present a novel underwater wearable computer enabling researchers to engage in an audio-based interaction between humans and dolphins. The design requirements are based on a research protocol developed by a team of marine biologists associated with the Wild Dolphin Project.

We investigate the potential of the Kinect depth-mapping camera for sign language recognition and verification for educational games for deaf children. We compare a prototype Kinect-based system to our current CopyCat system which uses colored gloves and embedded accelerometers to track children's hand movements. If successful, a Kinect-based approach could improve interactivity, user comfort, system robustness, system sustainability, cost, and ease of deployment. We collected a total of 1000 American Sign Language (ASL) phrases across both systems. On adult data, the Kinect system resulted in 51.5% and 76.12% sentence verification rates when the users were seated and standing respectively. These rates are comparable to the 74.82% verification rate when using the current(seated) CopyCat system. While the Kinect computer vision system requires more tuning for seated use, the results suggest that the Kinect may be a viable option for sign verification.

The CopyCat game is an interactive educational adventure game to help deaf children improve their language and memory abilities. As part of the CopyCat project, several computer-assisted language learning games have been designed, one of the games “Alien” is shown in Figure 1. Each game entails some sort of quest by the hero to collect items in order to solve a problem. In each quest, the child interacts with the hero (Iris the white cat) via American Sign Language (ASL) to warn her of a villain or identify where a hidden object is located. The child may view the tutor repeatedly if they so choose (see Figure 1). After the child talks to the hero, the child's signing is classified as correct or incorrect. If the child's signing is incorrect, a question mark appears above the hero's head to simulate misunderstanding by the hero, and the child must try again to communicate accurately. If the child's sign is correct, the hero, with the wave of a paw, “poofs” the villain, turning it into an innocuous item, and the hero continues on the quest.

We perform real-time American Sign Language (ASL) phrase verification for an educational game, CopyCat, which is designed to improve deaf children's signing skills. Taking advantage of context information in the game we verify a phrase, using Hidden Markov Models (HMMs), by applying a rejection threshold on the probability of the observed sequence for each sign in the phrase. We tested this approach using 1204 signed phrase samples from 11 deaf children playing the game during the phase two deployment of CopyCat. The CopyCat data set is particularly challenging because sign samples are collected during live game play and contain many variations in signing and disfluencies. We achieved a phrase verification accuracy of 83% compared to 90% real-time performance by a sign linguist. We report on the techniques required to reach this level of performance.

We have developed and deployed a multimedia museum installation that enables one or several users to interact with and collaboratively explore a 3D virtual environment while simultaneously providing an engaging and educational, theater-like experience for a larger crowd of passive viewers. This interactive theater experience consists of a large, immersive projection display, a touch screen display for gross navigation and three wireless, motion-sensing, hand-held controllers which allow multiple users to collaboratively explore a photorealistic virtual environment of Atlanta, Georgia and learn about Atlanta's history and the philanthropic legacy of many of Atlanta's prominent citizens.

We describe the activity recognition component of the Soldier Assist System (SAS), which was built to meet the goals of DARPA’s Advanced Soldier Sensor Information System and Technology (ASSIST) program. As a whole, SAS provides an integrated solution that includes on-body data capture, automatic recognition of soldier activity, and a multimedia interface that combines data search and exploration. The recognition component analyzes readings from six on-body accelerometers to identify activity. The activities are modeled by boosted 1D classifiers, which allows efficient selection of the most useful features within the learning algorithm. We present empirical results based on data collected at Georgia Tech and at the Army’s Aberdeen Proving Grounds during official testing by a DARPA appointed NIST evaluation team. Our approach achieves 78.7% for continuous event recognition and 70.3% frame level accuracy. The accuracy increases to 90.3% and 90.3% respectively when considering only the modeled activities. In addition to standard error metrics, we discuss error division diagrams (EDDs) for several Aberdeen data sequences to provide a rich visual representation of the performance of our system.

In this paper we present a concept for augmented reality entertainment, called AR Karaoke, where users perform their favorite dramatic scenes with virtual actors. AR Karaoke is the acting equivalent of traditional karaoke, where the goal is to facilitate an acting experience for the user that is entertaining for both the user and audience. Prototype implementations were created to evaluate various user interfaces and design approach reveal guidelines that are relevant to the design of mixed reality applications in the domains of gaming, performance, and entertainment.