Modelling and correcting for the impact of the gait cycle on touch screen typing accuracy

Walking and typing on a smartphone is an extremely common interaction. Previous research has shown that error rates are higher when walking than when stationary. In this paper we analyse the acceleration data logged in an experiment in which users typed whilst walking, and extract the gait phase angle. We find statistically significant relationships between tapping time, error rate and gait phase angle. We then use the gait phase as an additional input to an offset model, and show that this allows more accurate touch interaction for walking users than a model which considers only the recorded tap position

Modelling uncertainty in touch interaction

Touch interaction is an increasingly ubiquitous input modality on modern devices. It appears on devices including phones, tablets, smartwatches and even some recent laptops. Despite its popularity, touch as an input technology suffers from a high level of measurement uncertainty. This stems from issues such as the ‘fat finger problem’, where the soft pad of the finger creates an ambiguous contact region with the screen that must be approximated by a single touch point. In addition to these physical uncertainties, there are issues of uncertainty of intent when the user is unsure of the goal of a touch. Perhaps the most common example is when typing a word, the user may be unsure of the spelling leading to touches on the wrong keys. The uncertainty of touch leads to an offset between the user’s intended target and the touch position recorded by the device. While numerous models have been proposed to model and correct for these offsets, existing techniques in general have assumed that the offset is a deterministic function of the input. We observe that this is not the case — touch also exhibits a random component. We propose in this dissertation that this property makes touch an excellent target for analysis using probabilistic techniques from machine learning. These techniques allow us to quantify the uncertainty expressed by a given touch, and the core assertion of our work is that this allows useful improvements to touch interaction to be obtained. We show this through a number of studies. In Chapter 4, we apply Gaussian Process regression to the touch offset problem, producing models which allow very accurate selection of small targets. In the process, we observe that offsets are both highly non-linear and highly user-specific. In Chapter 5, we make use of the predictive uncertainty of the GP model when applied to a soft keyboard — this allows us to obtain key press probabilities which we combine with a language model to perform autocorrection. In Chapter 6, we introduce an extension to this framework in which users are given direct control over the level of uncertainty they express. We show that not only can users control such a system succesfully, they can use it to improve their performance when typing words not known to the language model. Finally, in Chapter 7 we show that users’ touch behaviour is significantly different across different tasks, particularly for typing compared to pointing tasks. We use this to motivate an investigation of the use of a sparse regression algorithm, the Relevance Vector Machine, to train offset models using small amounts of data

AZERTY amélioré: computational design on a national scale

International audienceFrance is the first country in the world to adopt a keyboard standard informed by computational methods, improving the performance, ergonomics, and intuitiveness of the keyboard while enabling input of many more characters. We describe a human-centric approach developed jointly with stakeholders to utilize computational methods in the decision process not only to solve a well-defined problem but also to understand the design requirements, to inform subjective views, or to communicate the outcomes. To be more broadly useful, research must develop computational methods that can be used in a participatory and inclusive fashion respecting the different needs and roles of stakeholders

Élaboration de la disposition AZERTY modernisée

Document de travail utilisé dans la rédaction de l'annexe F “Élaboration de la disposition AZERTY modernisée” de la norme AFNOR Z 71-300 : “Dispositions de clavier bureautique français”

Reliability of the Spinal Instability Neoplastic Score (SINS) among radiation oncologists: an assessment of instability secondary to spinal metastases

BACKGROUND: The Spinal Instability Neoplastic Score (SINS) categorizes tumor related spinal instability. It has the potential to streamline the referral of patients with established or potential spinal instability to a spine surgeon. This study aims to define the inter- and intra-observer reliability and validity of SINS among radiation oncologists. METHODS: Thirty-three radiation oncologists, across ten international sites, rated 30 neoplastic spinal disease cases. For each case, the total SINS (0-18 points), three clinical categories (stable: 0-6 points, potentially unstable: 7-12 points, and unstable: 13-18 points), and a binary scale (‘stable’: 0-6 points and ‘current or possible instability’; surgical consultation recommended: 7-18 points) were recorded. Evaluation was repeated 6-8 weeks later. Inter-observer agreement and intra-observer reproducibility were calculated by means of the kappa statistic and translated into levels of agreement (slight, fair, moderate, substantial, and excellent). Validity was determined by comparing the ratings against a spinal surgeon’s consensus standard. RESULTS: Radiation oncologists demonstrated substantial (κ = 0.76) inter-observer and excellent (κ = 0.80) intra-observer reliability when using the SINS binary scale (‘stable’ versus ‘current or possible instability’). Validity of the binary scale was also excellent (κ = 0.85) compared with the gold standard. None of the unstable cases was rated as stable by the radiation oncologists ensuring all were appropriately recommended for surgical consultation. CONCLUSIONS: Among radiation oncologists SINS is a highly reliable, reproducible, and valid assessment tool to address a key question in tumor related spinal disease: Is the spine ‘stable’ or is there ‘current or possible instability’ that warrants surgical assessment

Enumeration of islets by nuclei counting and light microscopic analysis

Author Manuscript 2011 May 1.Islet enumeration in impure preparations by conventional dithizone staining and visual counting is inaccurate and operator dependent. We examined nuclei counting for measuring the total number of cells in islet preparations, and we combined it with morphological analysis by light microscopy (LM) for estimating the volume fraction of islets in impure preparations. Cells and islets were disrupted with lysis solution and shear, and accuracy of counting successively diluted nuclei suspensions was verified with (1) visual counting in a hemocytometer after staining with crystal violet, and automatic counting by (2) aperture electrical resistance measurement and (3) flow cytometer measurement after staining with 7-aminoactinomycin-D. DNA content averaged 6.5 and 6.9 pg of DNA per cell for rat and human islets, respectively, in agreement with literature estimates. With pure rat islet preparations, precision improved with increasing counts, and samples with about greater than or equal to 160 islets provided a coefficient of variation of about 6%. Aliquots of human islet preparations were processed for LM analysis by stereological point counting. Total nuclei counts and islet volume fraction from LM analysis were combined to obtain the number of islet equivalents (IEs). Total number of IE by the standard method of dithizone staining/manual counting was overestimated by about 90% compared with LM/nuclei counting for 12 freshly isolated human islet research preparations. Nuclei counting combined with islet volume fraction measurements from LM is a novel method for achieving accurate islet enumeration.National Institutes of Health (U.S.) (Grant NCRR ICR U4Z 16606)National Institutes of Health (U.S.) (Grant R01-DK063108-01A1)National Institutes of Health (U.S.) (Grant NCRR ICR U42 RR0023244-01)Joslin Diabetes and Endocrinology Research Center (Grant DK36836)Diabetes Research & Wellness FoundationJuvenile Diabetes Research Foundation International (Islet Transplantation, Harvard Medical School

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Sketchplorer

This workshop paper discusses our mixed-initiative approach that enables designers to rapidly sketch and explore interactive layout designs. Although optimisation methods can attack very complex design problems, their insistence on precise objectives and a point optimum is a poor fit with sketching practices. Typical optimisation tools also fail to incorporate the human in the loop. Sketchplorer is a mixed-initiative sketching tool that uses a real-time layout optimiser. It automatically infers the designer's task to search for both local improvements to the current design and global (radical) alternatives. Using predictive models of sensorimotor performance and perception, it generates suggestions that interactively steer the designer towards more usable and aesthetic layouts without overriding them or demanding extensive input. While this position paper summarises our work from the mixed-initiative perspective, further details can be found in the original publication [4].Peer reviewe

A Participatory Design Process of a Robotic Tutor of Assistive Sign Language for Children with Autism

We present the participatory design process of a robotic tutor of assistive sign language for children with autism spectrum disorder (ASD). Robots have been used in autism therapy, and to teach sign language to neurotypical children. The application of teaching assistive sign language - the most common form of assistive and augmentative communication used by people with ASD - is novel. The robot's function is to prompt children to imitate the assistive signs that it performs. The robot was therefore co-designed to appeal to children with ASD, taking into account the characteristics of ASD during the design process: impaired language and communication, impaired social behavior, and narrow flexibility in daily activities. To accommodate these characteristics, a multidisciplinary team defined design guidelines specific to robots for children with ASD, which were followed in the participatory design process. With a pilot study where the robot prompted children to imitate nine assistive signs, we found support forthe effectiveness of the design. The children successfully imitated the robot and kept their focus on it, as measured by their eye gaze. Children and their companions reported positive experiences with the robot, and companions evaluated it as potentially useful, suggesting that robotic devices could be used to teach assistive sign language to children with ASD.Peer reviewe