Building magical realms: responses to pervasive and locative media technology

Abstract

This paper reports on 12 participatory design workshops involving 216 young people, aged 9 to 16. It discusses responses to existing and proposed locative and pervasive media technologies in gaming, mapping, gifting, game design, bodystorming, and collaborative storytelling activities. Issues of the technomagical in scenario planning are discussed.     

Exploring the use of design pattern maps for aligning new technical support to new clinical team meeting routines

We propose the collaborative activity of mapping design patterns against stakeholder values as a viable method for grounding conceptual design of information and communication technology (ICT) services for heterogeneous sets of stakeholders. Preliminary experiences from designing a case book service for video-mediated gastro-medical team meetings are presented. A diverse set of stakeholders and the challenge to apply novel technologies in a demanding environment have placed more responsibility on the Human Computer Interaction (HCI) team to conceptualise new work practices and their expected effects than what traditional participatory design projects typically entail. By combining the methodologies of genre analysis and pattern languages, design pattern maps have been used to conceptualise solutions that span both work and interface aspects of the solution and that match declared values of the stakeholders concerned. A series of mapping sessions with different stakeholders helped the inter-disciplinary project team to better define, what stakeholder values called for what new work patterns and what kind of supporting interaction design patterns these new work patterns in turn called for.     

Supporting Social Interaction in Care Environments: Exploring Stakeholder Perspectives on the Potential of Interactive Technology

This article explores care stakeholders’ perspectives on how interactive technology can help form socially active environments in residential care settings. Based on participatory workshops, involving representatives from multiple stakeholder groups, the authors identify a set of considerations relevant for design of social inclusion technology for care settings. The design considerations relate to the following topics: users, places, themes, value, and role. The authors also present three mock-ups emanating from the workshops, representing the participants’ visions as to how technology can contribute to social interaction by accommodating considerations related to the above topics. The results from this study highlight the importance of social inclusion technology being firmly anchored in the local and collaboratively produced care environment. In particular, their findings illustrate how the local—i.e., the wider social context in which the care residents live, and in which activities and things gain social meaning and value—can offer a rich design space and valuable source of inspiration for social inclusion technology. Potential negative implications of social inclusion technology are also briefly discussed.

The main contribution of this article is an increased understanding of the intimate relationship between designs for social inclusion and the wider social context in which care residents live.     

基于排列熵和支持向量机的癫痫发作预测研究

针对癫痫发作给病人带来的巨大伤害,为临床治疗留下足够空余时间,提出一个可以预测癫痫发作的系统模型。对21名癫痫病人进行研究,提取具有较低算法复杂度的排列熵构成特征向量,将其输入支持向量机（support vector machine,SVM）训练出学习模型,用来识别发作期样本,利用投票机制充分考虑病人差异来判断所处状态,最终实现癫痫的实时预测。结果表明,其中81%的发作可以提前平均50多分钟预测到,且具有较低的误报率。为癫痫发作预测系统的理论研究打下坚实基础。     

Thinking OutsideTheBox - Designing Smart Things with Autistic Children

ABSTRACT

This article offers a synopsis of and a critical reflection on the research project OutsideTheBox Rethinking Assistive Technology with Autistic Children. The aim of the 3-year project was to develop digital technology that would holistically respond to the complex life-worlds of autistic children, affording positive experiences that they could share with others. Through a series of long-term participatory design processes, smart objects were developed individually with nine children employing a wide range of different methods (e.g., Co-operative Inquiry, Future Workshops, Fictional Inquiry, Magic Workshops, Drama and Making & Digital Fabrication). In this article are presented the cases of all children worked with and tie them together by a critical reflection across them. The discussion offers insights along three main themes: we a) substantiate the argument for a theoretical shift in conceptualizing roles for technology in the lives of disabled people, b) discuss our methodological contributions in participatory design processes and c) propose alternative, participatory approaches to evaluate outcomes.     

An Open Road Evaluation of a Self-Driving Vehicle Human–Machine Interface Designed for Visually Impaired Users

ABSTRACT

Fully autonomous or “self-driving” vehicles are an emerging technology that may hold tremendous mobility potential for individuals who are visually impaired who have been previously disadvantaged by an inability to operate conventional motor vehicles. Prior studies however, have suggested that these consumers have significant concerns regarding the accessibility of this technology and their ability to effectively interact with it. We present the results of a quasi-naturalistic study, conducted on public roads with 20 visually impaired users, designed to test a self-driving vehicle human–machine interface. This prototype system, ATLAS, was designed in participatory workshops in collaboration with visually impaired persons with the intent of satisfying the experiential needs of blind and low vision users. Our results show that following interaction with the prototype, participants expressed an increased trust in self-driving vehicle technology, an increased belief in its likely usability, an increased desire to purchase it and a reduced fear of operational failures. These findings suggest that interaction with even a simulated self-driving vehicle may be sufficient to ameliorate feelings of distrust regarding the technology and that existing technologies, properly combined, are promising solutions in addressing the experiential needs of visually impaired persons in similar contexts.     

癫痫脑电的互信息和同步性分析

脑电（EEG）分析是研究癫痫的一个重要手段。以临床采集的健康对象和癫痫患者的头皮EEG为研究对象,计算不同导联EEG数据之间的排序互信息,结果表明癫痫患者不同导联之间的互信息明显高于健康对象,因此,排序互信息可以作为癫痫疾病诊断的重要特征。以排序互信息为依据,对癫痫脑电进行了同步性的分析,结果表明癫痫患者左脑区域内、右脑区域内及左右脑区之间的信息交流明显增强,即其同步性强于健康对象。互信息和同步性的分析方法还可对癫痫发作前期和发作阶段的EEG进行分析,对癫痫发作作出预测。     

A Series-elastic Robot for Back-pain Rehabilitation

This paper addresses the robot-assisted rehabilitation of back pain, an epidemic health problem affecting a large portion of the population. The design is composed of two springs in series connected to an end-effector via a pair of antagonistic cables. The spring and cable arrangement forms an elastic coupling from the actuator to the output shaft. An input-output torque model of the series-elastic mechanism is established and studied numerically. The study also illustrates the variation of the mechanism’s effective stiffness by changing the springs’ position. In addition, we built a prototype of the robotic mechanism and design experiments with a robotic manipulator to experimentally investigate its dynamic characteristics. The experimental results confirm the predicted elasticity between the input motion and the output torque at the end-effector. We also observe an agreement between the data generated by the torque model and data collected from the experiments. An experiment with a full-scale robot and a human subject is carried out to investigate the human-robot interaction and the mechanism behavior.

     

A Game-theoretic approach to analyze interacting actors in GRL goal models

Goal-oriented requirements engineering aims to capture desired goals and strategies of relevant stakeholders during early requirements engineering stages, using goal models. Goal-oriented modeling techniques support the analysis of system requirements (especially non-functional ones) from an operationalization perspective, through the evaluation of alternative design options. However, conflicts and undesirable interactions between requirements produced from goals are inevitable, especially as stakeholders often aim for different objectives. In this paper, we propose an approach based on game theory and the Goal-oriented Requirement Language (GRL) to reconcile interacting stakeholders (captured as GRL actors), leading to reasonable trade-offs. This approach consists in building a payoff bimatrix that considers all actor’s valid GRL strategies, and computing its Nash equilibrium. Furthermore, we use two optimization techniques to reduce the size of the payoff bimatrix, hence reducing the computational cost of the Nash equilibrium. The approach goes beyond existing work by supporting nonzero-sum games, multiple alternatives, and inter-actor dependencies. We demonstrate the applicability of our game-theoretic modeling and analysis approach using a running example and two GRL models from the literature, with positive results on feasibility and applicability, including performance results.

     

CAVEAT Exemplar: Participatory Design in a Non-Profit Volunteer Organisation

This paper reports a university course-based case study undertaken with a volunteer organisation. Our goals were to explore the use of participatory design in a non-profit volunteer setting; to reflect on the experience of learning and applying participatory methodologies; and to create a prototype, using off-the-shelf database software, that could become a sustainable organisational information system. We found system design methodologies that stress cooperation and consensus especially appropriate when working with volunteers, who expect control over their work in exchange for their time and effort. The Future Workshop was particularly valuable in developing group insight into work and consensus around system priorities. The study resulted in a prototype which has evolved, through in-house refinement, into a working system.     

Participatory heritage innovation: designing dialogic sites of engagement

Abstract

Innovations in digital cultural communication for museums challenge us to develop appropriate methods for participation in curatorial processes and to rethink the role of audiences inside exhibitions. The article explores the potentials of scaffolding sites of dialogue and creative engagement through the design process and final exhibition. It draws upon experiences from an interactive exhibition project, Digital Natives, in which we combined principles from Participatory Design with issues of contemporary digital culture to explore possibilities for creating heritage innovation. We suggest three critical stages of the dialogic design process in which engagement between stakeholders, researchers, and audiences can be central to shaping and transforming future conceptions of digital cultural heritage, through process and final exhibition. In this way, we argue that a participatory design anthropological approach to digital culture can expand opportunities for heritage innovation through technological means of engagement in museums.     

Mapping and mining interictal pathological gamma (30-100 Hz) oscillations with clinical intracranial EEG in patients with epilepsy

Localizing an epileptic network is essential for guiding neurosurgery and antiepileptic medical devices as well as elucidating mechanisms that may explain seizure-generation and epilepsy. There is increasing evidence that pathological oscillations may be specific to diseased networks in patients with epilepsy and that these oscillations may be a key biomarker for generating and indentifying epileptic networks. We present a semi-automated method that detects, maps, and mines pathological gamma (30-100 Hz) oscillations (PGOs) in human epileptic brain to possibly localize epileptic networks. We apply the method to standard clinical iEEG (<100 Hz) with interictal PGOs and seizures from six patients with medically refractory epilepsy. We demonstrate that electrodes with consistent PGO discharges do not always coincide with clinically determined seizure onset zone (SOZ) electrodes but at times PGO-dense electrodes include secondary seizure-areas (SS) or even areas without seizures (NS). In 4/5 patients with epilepsy surgery, we observe poor (Engel Class 4) postsurgical outcomes and identify more PGO-activity in SS or NS than in SOZ. Additional studies are needed to further clarify the role of PGOs in epileptic brain.     

Adapting Virtual Reality for the Participatory Design of Work Environments

This paper describes the evolution of a standard PC-based virtual reality tool which has been adapted for the participatory design of work environments. Tool features, method of control and combination with other participatory design tools are investigated in the context of a particular design situation. This research is aimed at participatory design facilitators to aid in the adaptation of similar virtual reality systems for a similar purpose. The context of this work is the Envisionment Workshop, in which a group of workers participate with design experts in using full-scale modelling, pedagogical drama, and democratic meetings to (re)design their workplace. A series of prototypes have been developed and tested during the design of a new university in the region using a case study methodology to provide high ecological validity. These were preceded by a task analysis, brainstorming and pilot study. The results suggest that such a tool can be constructed and used successfully by a small group of people using projected virtual reality. However larger groups suffer from a bottleneck at the input devices such that a virtual reality expert must take control and build what the participants wish. This revised version was published online in August 2006 with corrections to the Cover Date.     

癫痫脑电的递归确定性分析

利用排序递归图的分析方法对癫痫脑电进行了确定性(DET)的分析,得出癫痫头皮脑电(EEG)的DET高于健康EEG。DET特征的差异性在局部导联上更明显,局部导联的DET特征可以作为癫痫疾病的自动诊断特征。通过分析发作阶段和发作间隙皮层脑电(ECoG)的DET,得出整个频带的DET差别不大,而在beta频带,发作阶段的确定性明显高于发作间隙的DET。Beta频带的DET特征可以作为癫痫发作的预测特征。研究结果为癫痫疾病的自动诊断和癫痫发作预测提供了理论依据。     

Performance analysis of power and power variance for classification,detection and localization of epileptic multi-channel EEG

There are a large number of data sets of EEG signal for which, it is difficult to judge and monitor brain activity through observations. Epilepsy is a disorder in which a recurrent and sudden malfunction of the brain is characterized. It is proposed to classify, detect and localize Epileptic multi-channel EEG through various power and novel power variance features non-invasively. This work presents power spectral estimation (PSE) using time–frequency analysis of EEG signals in both parametric (FFT) and non-parametric methods (i.e. Welch, Burg, Covariance, MUSIC and Yule–Walker). To examine the robustness of power features for different methods, the analysis of p value is performed. The detection of epileptic seizure is classified using different kernels through SVM. It is observed from the PSE that the power features have higher values in epileptic subjects as compared to non-epileptic subjects. Amongst all the parametric and non-parametric methods, the MUSIC method gives the highest average power. Sensitivity, specificity, and classification accuracy are 100% for Welch, Burg, Covariance, and Yule–Walker methods while MUSIC and FFT methods deliver 98.73 and 99.52% respectively. The novelty is introduced through the quantification of power and power variance robust feature region/lobe-wise. This quantification is used for the localization of 25 epileptic subjects. Analysis of the parametric and non-parametric PSD methods for extraction of power and power variance features is not used by any study. These are effectively utilized for detection and localization of epilepsy non-invasively.

     

Genetic programming of conventional features to detect seizure precursors

This paper presents an application of genetic programming (GP) to optimally select and fuse conventional features (C-features) for the detection of epileptic waveforms within intracranial electroencephalogram (IEEG) recordings that precede seizures, known as seizure precursors. Evidence suggests that seizure precursors may localize regions important to seizure generation on the IEEG and epilepsy treatment. However, current methods to detect epileptic precursors lack a sound approach to automatically select and combine C-features that best distinguish epileptic events from background, relying on visual review predominantly. This work suggests GP as an optimal alternative to create a single feature after evaluating the performance of a binary detector that uses: (1) genetically programmed features; (2) features selected via GP; (3) forward sequentially selected features; and (4) visually selected features. Results demonstrate that a detector with a genetically programmed feature outperforms the other three approaches, achieving over 78.5% positive predictive value, 83.5% sensitivity, and 93% specificity at the 95% level of confidence.     

On facilitating knowledge transfer in software design

This paper presents a discussion of the facilitation of expertise sharing among software design stakeholders. LOUIS, a prototype research tool, helps to capture much of the contextual information and knowledge in early design meetings that are very often lost soon after the meetings are over. Using LOUIS as a basis, we consider knowledge and skill transfer effects in software design tasks. Results from trials indicate that, although not entirely sufficient, process-related knowledge, in the form of argumentation, is useful to software designers who have reason to re-use that knowledge. A list of recommendations on how those knowledge transfer effects can be further facilitated is provided.     

A multilayered ergonomic intervention program on reducing musculoskeletal disorders in an industrial complex: A dynamic participatory approach

Work-related musculoskeletal disorders (WMSDs) are closely identified with common complaints in different workplaces. This study aimed to implement an intervention program through which ergonomic measures were dynamically localized in industry. An interventional study, including three basic layers, namely, training workshops, participatory ergonomics (PE), and workstation redesign was fulfilled in an Iranian steel manufacturing complex from 2017 to 2020. A steering committee (SC) was formed following several meetings held for clarification of the project to the management team. The SC members then attended four organized workshops managed by an ergonomics specialist. Afterwards, the basics of ergonomics were transferred to action groups. After developing ergonomic assessment tools, the ergonomic problems were prioritized and numerous positive changes were made by the action groups. The findings of the tailored checklists revealed a load of WMSDs risk factors. All the three layers of the program were implemented as initiated. Ergonomics training workshops were then held and significant differences were observed between the participants' pre/posttest mean scores in all workshops (p < 0.001). Moreover, PE measures were exercised at all levels of the organization inducing enthusiastic motivation of the workforce to consider ergonomic requirements in the workplace. Consequently, the workers' innovative ideas and the managerial support yielded diverse workstation redesigns due to a growth in either the workers' ergonomics awareness or participatory culture grounding. A multilayered ergonomic intervention was implemented in this study. In conclusion, a multifaceted long-term follow-up intervention program could be applied to enhance workers’ health status and to raise system productivity.     

Bellcore's user-centred-design support centre

Abstract

Bellcore recently replaced its small laboratory that was designed primarily for formal testing of software usability. The new facility is a suite of rooms that handles multiple, independent activities. More importantly, the new space is a manifestation of our philosophy that the best approach to interface design is the cultivation of eclectic design practices early in and throughout the software development process. To that end, the new lab supports other kinds of user-centred design (UCD) activities in addition to formal testing of computerized prototypes of software interfaces. To encourage participatory design, nearly all the rooms are large enough for design meetings, contain entire walls of movable whiteboards, and have small tables so design teams can huddle over paper prototypes and task layouts. In this article we describe the new lab, the rationales behind its features, and the process by which it was designed.     

A tunable support vector machine assembly classifier for epileptic seizure detection

Automating the detection of epileptic seizures could reduce the significant human resources necessary for the care of patients suffering from intractable epilepsy and offer improved solutions for closed-loop therapeutic devices such as implantable electrical stimulation systems. While numerous detection algorithms have been published, an effective detector in the clinical setting remains elusive. There are significant challenges facing seizure detection algorithms. The epilepsy EEG morphology can vary widely among the patient population. EEG recordings from the same patient can change over time. EEG recordings can be contaminated with artifacts that often resemble epileptic seizure activity. In order for an epileptic seizure detector to be successful, it must be able to adapt to these different challenges. In this study, a novel detector is proposed based on a support vector machine assembly classifier (SVMA). The SVMA consists of a group of SVMs each trained with a different set of weights between the seizure and non-seizure data and the user can selectively control the output of the SVMA classifier. The algorithm can improve the detection performance compared to traditional methods by providing an effective tuning strategy for specific patients. The proposed algorithm also demonstrates a clear advantage over threshold tuning. When compared with the detection performances reported by other studies using the publicly available epilepsy dataset hosted by the University of BONN, the proposed SVMA detector achieved the best total accuracy of 98.72%. These results demonstrate the efficacy of the proposed SVMA detector and its potential in the clinical setting.