A Framework for Discovery and Diagnosis of Behavioral Transitions in Event-streams

Date stream mining techniques can be used in tracking user behaviors as they attempt to achieve their goals. Quality metrics over stream-mined models identify potential changes in user goal attainment. When the quality of some data mined models varies significantly from nearby models—as defined by quality metrics—then the user’s behavior is automatically flagged as a potentially significant behavioral change. Decision tree, sequence pattern and Hidden Markov modeling being used in this study. These three types of modeling can expose different aspect of user’s behavior. In case of decision tree modeling, the specific changes in user behavior can automatically characterized by differencing the data-mined decision-tree models. The sequence pattern modeling can shed light on how the user changes his sequence of actions and Hidden Markov modeling can identifies the learning transition points. This research describes how model-quality monitoring and these three types of modeling as a generic framework can aid recognition and diagnoses of behavioral changes in a case study of cognitive rehabilitation via emailing. The date stream mining techniques mentioned are used to monitor patient goals as part of a clinical plan to aid cognitive rehabilitation. In this context, real time data mining aids clinicians in tracking user behaviors as they attempt to achieve their goals. This generic framework can be widely applicable to other real-time data-intensive analysis problems. In order to illustrate this fact, the similar Hidden Markov modeling is being used for analyzing the transactional behavior of a telecommunication company for fraud detection. Fraud similarly can be considered as a potentially significant transaction behavioral change

Technology to encourage meaningful activities following brain injury

Background: Cognitive and behavioural difficulties after acquired brain injury (ABI) may lead to reduced engagement in leisure and social activities. Increasing participation is a goal of neuropsychological rehabilitation and assistive and behaviour change technology can play an important role in this. Focus groups and interviews were conductive with brain injury rehabilitation stakeholders (n = 24): people with ABI (n = 9), family members (n = 3) and care providers (n = 12) in order to understand the barriers to engaging in meaningful activities and what helps to overcome these barriers. A collaborative thematic analysis was performed by a multi-disciplinary research team using an approach based on Grounded Theory. Results: Four central, interlinked, barriers were found: Access, Cognitive Difficulties, Anticipation (of Physical or Cognitive Difficulties) and Motivation. To overcome these barriers, participants cited themes such as External Motivation from both Other People and Technology, Maintaining Momentum and different aspects of Being Planful. Conclusions: The results point to future directions for the purposeful development of effective assistive technology for this user group. Technology that is social, persuasive, adapts to individual needs and supports people to plan activities are likely to be particularly useful within neuropsychological rehabilitation. Implications For Rehabilitation: Adults with ABI and their carers describe problems accessing activities, cognitive difficulties, anticipationof physical or cognitive difficulties and low motivation as the key barriers to undertaking meaningfulactivities. Current solutions are external prompting, maintaining momentum and being planful. This detailed qualitative analysis of a diverse group of carers and service users allows insight into theassistive technologies that could aid rehabilitation

An Event-based Analysis Framework for Open Source Software Development Projects

The increasing popularity and success of Open Source Software (OSS) development projects has drawn significant attention of academics and open source participants over the last two decades. As one of the key areas in OSS research, assessing and predicting OSS performance is of great value to both OSS communities and organizations who are interested in investing in OSS projects. Most existing research, however, has considered OSS project performance as the outcome of static cross-sectional factors such as number of developers, project activity level, and license choice. While variance studies can identify some predictors of project outcomes, they tend to neglect the actual process of development. Without a closer examination of how events occur, an understanding of OSS projects is incomplete. This dissertation aims to combine both process and variance strategy, to investigate how OSS projects change over time through their development processes; and to explore how these changes affect project performance. I design, instantiate, and evaluate a framework and an artifact, EventMiner, to analyze OSS projects’ evolution through development activities. This framework integrates concepts from various theories such as distributed cognition (DCog) and complexity theory, applying data mining techniques such as decision trees, motif analysis, and hidden Markov modeling to automatically analyze and interpret the trace data of 103 OSS projects from an open source repository. The results support the construction of process theories on OSS development. The study contributes to literature in DCog, design routines, OSS development, and OSS performance. The resulting framework allows OSS researchers who are interested in OSS development processes to share and reuse data and data analysis processes in an open-source manner

Virtual environments for stroke rehabilitation: examining a novel technology against end-user, clinical and management demands with reference to UK care provision

In the field of post-stroke rehabilitation, there appears to be growing interest in the use of virtual reality (VR)-based systems as adjunct technologies to standard therapeutic practices. The limitations and the potentials of this technology are not, however, generally well understood. The present study thus seeks to determine the value of the technology with reference to end-user requirements by surveying and evaluating its application against a variety of parameters: user focus, clinical effectiveness, marketability and contextual meaningfulness, etc. A key theme in the research considers how a technology developed internationally might interface with care provision demands and cultures specific to the United Kingdom. The barriers to innovation entry in this context are thus examined. Further practical study has been conducted in the field with a small sample of post-stroke rehabilitation patients. The data garnered from these enquiries have informed a detailed system analysis, a strategy for innovation and a broad theoretical discussion as to the effectiveness of the technology in delivering VR environments by which the patient can undertake ‘meaningful’ therapeutic activities. The data reveal that there does appear to be clinical value in using this technology, yet establishing its maximal value necessitates greater integrity among clinicians and engineers, and the furthering of progressive channels for innovation by public health administrators

SUPPORTING THERAPY-CENTERED GAME DESIGN FOR BRAIN INJURY REHABILITATION

Brain injuries (BI) are a major public health issue. Many therapists who work with patients who have had a BI include games to ameliorate boredom associated with repetitive rehabilitation. However, designing effective, appropriate, and engaging games for BI therapy is challenging. The challenge is especially manifested when considering how to consolidate the different mindsets and motivations among key stakeholders; i.e., game designers and therapists. In this dissertation, I investigated the ideation, creation, and evaluation of game design patterns and a design tool, GaPBIT (Game Design Patterns for BI Therapy) that leveraged patterns to support ideation of BI therapy game concepts and facilitate communication among designers and therapists. Design patterns, originated from the work of Christopher Alexander, provide a common design language in a specific field by documenting reusable design concepts that have successfully solved recurring problems. This investigation involved four overlapping phases. In Phase One, I interviewed 11 professional game designers focused on games for health (serious games embedded with health-related goals) to explore how they perceived and approached their work. In Phase Two, I identified 25 therapy-centered game design patterns through analyzing data about game use in BI therapy. Based on those patterns, in Phase Three I created and iterated the GaPBIT prototype through user studies. In Phase Four, I conducted quasi-experimental case studies to establish the efficacy and user experience of GaPBIT in game design workshops that involved both game designers and therapists. During the design workshops, the design patterns and GaPBIT supported exploration of game design ideas and effectively facilitated discussion among designers and therapists. The results also indicated that these tools were especially beneficial for novice game designers. This work significantly promotes game design for BI rehabilitation by providing designers and therapists with easier access to the information about requirements in rehabilitation games. Additionally, this work modeled a novel research methodology for investigating domains where balancing the role of designers and other stakeholders is particularly important. Through a “practitioner-centered” process, this work also provides an exemplar of investigating technologies that directly address the information needs of professional practitioners

Participation-focussed evaluation: Impact on practice

Evaluation is a keystone in the process of rehabilitation that is used to plan and monitor holistic, client-centred, goal-directed programs. However, many common assessment tools do not fit well with the specific expertise of occupational therapists (OTs). Dynamic assessment uses interactions with clients as a context to both observe current performance and test possibilities for intervention. In this way, OTs may substantiate their clinical reasoning. Methods. This study aimed to examine OTs’ implementation of a dynamic assessment of participation called COMPLEAT©. Participants were 14 OTs with varied experience, and 29 of their younger adult (<65 years) clients with diverse aetiologies and sequelae of brain injury. Data were collected from multiple sources in a process from introducing the OTs to COMPLEAT© and providing basic training, to interpreting their observations. Two phases of analyses examined the sociocultural influences on the implementation of COMPLEAT©, and the strategies used with clients of varying levels of participation restriction. Results. From a sociocultural perspective, the OTs (i) facilitated their clients’ participation through both direct responses and enabling environmental supports, (ii) brought to the process experiences and views on working with clients and using standardised assessments, and (iii) utilised COMPLEAT© according to their roles and experience. Overall, they facilitated participation using complex combinations of responses according to clients’ levels of participation restriction. Conclusions. Dynamic assessment, and COMPLEAT© in particular, has application to substantiating OTs’ clinical reasoning and expertise in participation. With this evidence, OTs might promote a focus on participation within their rehabilitation teams, consolidate their teams’ perceptions of their roles, and further develop assessments that support the planning and implementation of interventions consistent with the theoretical foundations of OT

Surveying Persons with Disabilities: A Source Guide

In 2003, The National Institute on Disability and Rehabilitation Research (NIDRR) funded a Rehabilitation Research and Training Center on Disability Demographics and Statistics (StatsRRTC) at Cornell University‘s Employment and Disability Institute (EDI). The goal of the Center is to ―explore the reliability of existing data sources and collection methods and evaluate ways to improve and expand current data collection efforts‖ (EDI 2008). As a collaborator with the StatsRRTC, Mathematica Policy Research, Inc. (MPR), has been working on a project that identifies the strengths and limitations in existing disability data collection in both content and data collection methodology. The intended outcomes of this project include expanding and synthesizing knowledge of best practices and the extent to which existing data use those practices, informing the development of data enhancement options, and contributing to a more informed use of existing data

Proceedings of the 9th international conference on disability, virtual reality and associated technologies (ICDVRAT 2012)

The proceedings of the conferenc

Investigating cognition in chronic opioid use: Potential role for the gut microbiota

Impairment in cognitive functioning is a core component of opioid dependence due to its importance in the course of addiction and its role in treatment, but the effect of opioid use on cognition in individuals undergoing early stages of treatment is under examined, particularly in the Australian population. Although existing pharmacological options have demonstrated some efficacy in treating opioid dependence, they are limited in their ability to treat the cognitive dysfunction present in opioid dependent individuals. Hence, there is a need for novel treatment options that address these limitations. The commensal gut microbiota can engage in bidirectional communication with the brain and thus influence brain function, including cognition. Dysbiosis of the microbiota has been reported in several areas of addiction and concomitant cognitive impairment, and may serve as a target for potential future novel treatments. The effect of opioid use on the gut microbiota is inconclusive, however. The present thesis aimed to: a) investigate cognition in individuals with a history of chronic opioid use during the early stages of rehabilitation treatment in an Australian setting; b) examine the effect of opioid use on the gut microbiota, and; c) outline the functional potential of the gut microbiota in opioid use and how it may relate to key signalling pathways of the microbiota-gut-brain axis. In Chapter 2, Australian participants at early stages of community-based rehabilitative treatment (including treatment with methadone or buprenorphinenaloxone, BNX) underwent neurocognitive testing. Results demonstrated impaired cognitive functioning compared to the general population, but no significant differences between performance in BNX compared to methadone-treated participants. BNX treatment was associated with a longer length of stay, which could indicate greater treatment adherence. The potential influence of treatment and non-treatment related parameters were also examined. Treatment related factors (e.g., time since last dose, life-time length of treatment) had a significant relationship with cognitive performance in BNX-treated participants, but not methadone treated participants. Neurocognitive performance was also significantly influenced by non-treatment related demographics factors, such as age and BMI. Together, these findings demonstrate cognitive impairment in people undergoing residential rehabilitation for opioid addiction and highlight treatment and demographics parameters that could potentially influence cognitive outcomes and should be considered in future studies. In Chapter 3, a systematic literature review was conducted to investigate the effect of opioids on the gut microbiota. Results demonstrated that opioid use resulted in dysbiosis of the gut microbiota, and identified specific microbes that were repeatedly dysbiotic across clinical and preclinical studies for the first time. Opioid use also resulted in alterations to key signalling pathways of the microbiota-gut-brain axis, suggesting the potential for opioid induced dysbiosis of the gut microbiota to influence cognition. These results may have significant implications for future research aiming to better understand the pathology of opioid dependence, and may inform the development of future novel treatments that improve the lives of people with opioid dependence