Eunjeong Park

Reconfigurable Service Composition and Categorization for Power-Aware Mobile Computing

The requirement of agile adaptation to varying resource constraints in mobile systems motivates the use of a service-oriented architecture (SOA), which can support the composition of two or more services to form a complex service. In this paper, we propose SOA-based middleware to support QoS control of mobile applications and to configure an energy-efficient service composition graph. We categorize services into two layers: functionality-centric services, which are connected to create a complex service to meet the users intentions, and resource-centric services, which undertake distributed functionality-centric services in a way that increases the success rate of service composition while reducing contention at specific service nodes. We also present a service routing algorithm to balance the resource consumption of service providers on a service-overlay network. Through simulation of power-aware service composition using a realistic model based on ns-2 and traced data, we demonstrate that our approach can help both the mobile devices and the servers in a service-overlay network to reduce energy consumption without an increase in response time.

Facilitating Stroke Management using Modern Information Technology

BACKGROUND AND PURPOSE Information technology and mobile devices may be beneficial and useful in many aspects of stroke management, including recognition of stroke, transport and triage of patients, emergent stroke evaluation at the hospital, and rehabilitation. In this review, we address the contributions of information technology and mobile health to stroke management. SUMMARY OF ISSUES Rapid detection and triage are essential for effective thrombolytic treatment. Awareness of stroke warning signs and responses to stroke could be enhanced by using mobile applications. Furthermore, prehospital assessment and notification could be streamlined for use in telemedicine and teleradiology. A mobile telemedicine system for assessing the National Institutes of Health Stroke Scale scores has shown higher correlation and fast assessment comparing with face-to-face method. Because the benefits of thrombolytic treatment are time-dependent, treatment should be initiated as quickly as possible. In-hospital communication between multidisciplinary team members can be enhanced using information technology. A computerized in-hospital alert system using computerized physician-order entry was shown to be effective in reducing the time intervals from hospital arrival to medical evaluations and thrombolytic treatment. Mobile devices can also be used as supplementary tools for neurologic examination and clinical decision-making. In post-stroke rehabilitation, virtual reality and telerehabilitation are helpful. Mobile applications might be useful for public awareness, lifestyle modification, and education/training of healthcare professionals. CONCLUSIONS Information technology and mobile health are useful tools for management of stroke patients from the acute period to rehabilitation. Further improvement of technology will change and enhance stroke prevention and treatment.

Development of Smartphone Application That Aids Stroke Screening and Identifying Nearby Acute Stroke Care Hospitals

Purpose The benefits of thrombolytic treatment are time-dependent. We developed a smartphone application that aids stroke patient self-screening and hospital selection, and may also decrease hospital arrival time. Materials and Methods The application was developed for iPhone and Android smartphones. Map data for the application were adopted from the open map. For hospital registration, a web page (http://stroke119.org) was developed using PHP and MySQL. Results The Stroke 119 application includes a stroke screening tool and real-time information on nearby hospitals that provide thrombolytic treatment. It also provides information on stroke symptoms, thrombolytic treatment, and prescribed actions when stroke is suspected. The stroke screening tool was adopted from the Cincinnati Prehospital Stroke Scale and is displayed in a cartoon format. If the user taps a cartoon image that represents abnormal findings, a pop-up window shows that the user may be having a stroke, informs the user what to do, and directs the user to call emergency services. Information on nearby hospitals is provided in map and list views, incorporating proximity to the users location using a Global Positioning System (a built-in function of smartphones). Users can search for a hospital according to specialty and treatment levels. We also developed a web page for hospitals to register in the system. Neurology training hospitals and hospitals that provide acute stroke care in Korea were invited to register. Seventy-seven hospitals had completed registration. Conclusion This application may be useful for reducing hospital arrival times for thrombolytic candidates.

Selective grid access for energy-aware mobile computing

Conservation of battery power is one of the main issues in mobile computing. In this paper, we propose to exploit a grid infrastructure to extend the battery life of mobile devices based on the contexts of mobile applications, devices, and grid systems. In doing so, we present a framework, called SGA (selective grid access), to optimally utilize the limited resources of mobile devices and grids. SGA aims to reconfigure the placement of mobile applications on either the mobile device or grid nodes and to adjust QoS level according to the current context of the residual energy and the resource availability of the grids. Simulation-based experiments show that as the number of applications increases, the SGA-based scheme greatly reduces the energy consumption and response time in comparison with the traditional proxy-based approach.

Use of a handheld, computerized device as a decision support tool for stroke classification

Background:  The Trial of ORG 10172 in Acute Stroke Treatment (TOAST) classification has been widely used to determine etiology of ischemic stroke. However, interrater reliability is known to be modest. The complexity of abstraction and the interpretation of various clinical and laboratory data might limit the accuracy of the TOAST classification. In this study, we developed a computerized clinical decision support system for stroke classification that can be used in a handheld device and tested whether this system can improve diagnostic accuracy and reliability.

A Service-Oriented Medical Framework for Fast and Adaptive Information Delivery in Mobile Environment

The need for fast treatment of patients in critical conditions motivates the use of mobile devices to provide prompt and consistent communication between hospitals and physicians. We propose a framework that supports ubiquitous access to medical systems using personalized mobile services and integrated medical systems. The proposed service-oriented medical framework provides dynamically composed services that are adapted to contextual variables such as the users role, the network bandwidth, and resources available at mobile devices while supporting task allocation in distributed servers for massive resource-consuming services. It also manages accurate patient data by integrating local medical systems using medical information standards such as Digital Imaging and Communications in Medicine and Health Level 7. We have demonstrated the effectiveness of our framework by building a prototype of context-based adaptation of computerized tomography image retrieval for acute stroke treatments, which allows images to be viewed on mobile devices with WiMax wireless network. The proposed medical framework reduces hospital delays of patients and facilitates treatments in the absence of medical specialists.

An Objective Pronator Drift Test Application (iPronator) Using Handheld Device

Background The pronator drift test is widely used to detect mild arm weakness. We developed an application that runs on a handheld device to objectify the pronator drift test and investigated its feasibility in stroke patients. Methods The iPronator application, which uses the built-in accelerometer in handheld devices, was developed. We enrolled acute ischemic stroke patients (n = 10) with mild arm weakness and healthy controls (n = 10) to validate the iPronator. In addition to conventional neurological examinations, the degree of average, maximum, and oscillation in drift and pronation were measured and compared using the iPronator. Follow-up tests using the iPronator were also conducted in the patient group one week later. Results There was a strong correlation between the average degree of pronation and drift measured by the iPronator (r = 0.741, p<0.001). The degrees of average and maximum in pronation were greater in the patient group than in the control group [in average, 28.9°, interquartile range (IQR) 18.7–40.3 vs. 3.8° (IQR 0.3–7.5), p<0.001], in maximum, 33.0° (IQR 24.0–52.1) vs. 6.2° (IQR 1.4–9.4), p<0.001]. The degree of oscillation in pronation was not different between the groups (p = 0.166). In drift, the degrees of average, maximum, and oscillation were greater in the patient group. In stroke patients, a follow-up study at one week revealed improvements in the degrees of pronation and drift compared with baseline parameters. Conclusions The iPronator can reliably detect mild arm weakness of stroke patients and was also useful in detecting functional recovery for one week in patients with acute stroke.

Cooperative Reconfiguration of Software Components for Power-Aware Mobile Computing

Mobile applications require software reconfiguration to improve resource usage and availability. We propose a power-aware reconfiguration scheme that (1) moves energy-demanding applications to proxy servers, and (2) adjusts the fidelity of mobile applications as resources diminish. We formulate a cooperative reconfiguration plan which determines when, where, and which components should be deployed and have their fidelity controlled, so as to minimize the power consumption of mobile devices and to utilize the system resources of servers efficiently. We then construct a graph-theoretic model of the cost of migrating components to one proxy server or to a cluster of servers. In this model, changes to the residual energy of mobile devices, available server resources, and the wireless network bandwidth can all accelerate or decelerate the migration and fidelity control of applications. We suggest an approximation algorithm that achieves a near-optimal solution in terms of energy consumption. Our proposal will support mobile applications which require large amount of computation and need to maintain their services for an extended time such as video conferencing, multimedia e-mail, and real-time navigation. Simulation-based experiments verify that our scheme is an efficient way to extend the battery life of mobile devices and to improve the response time of mobile applications.

Unobtrusive and Continuous Monitoring of Alcohol-impaired Gait Using Smart Shoes

BACKGROUND Alcohol ingestion influences sensory-motor function and the overall well-being of individuals. Detecting alcohol-induced impairments in gait in daily life necessitates a continuous and unobtrusive gait monitoring system. OBJECTIVES This paper introduces the development and use of a non-intrusive monitoring system to detect changes in gait induced by alcohol intoxication. METHODS The proposed system employed a pair of sensorized smart shoes that are equipped with pressure sensors on the insole. Gait features were extracted and adjusted based on individuals gait profile. The adjusted gait features were used to train a machine learning classifier to discriminate alcohol-impaired gait from normal walking. In experiment of pilot study, twenty participants completed walking trials on a 12 meter walkway to measure their sober walking and alcohol-impaired walking using smart shoes. RESULTS The proposed system can detect alcohol-impaired gait with an accuracy of 86.2 % when pressure value analysis and person-dependent model for the classifier are applied, while statistical analysis revealed that no single feature was discriminative for the detection of gait impairment. CONCLUSIONS Alcohol-induced gait disturbances can be detected with smart shoe technology for an automated monitoring in ubiquitous environment. We demonstrated that personal monitoring and machine learning-based prediction could be customized to detect individual variation rather than applying uniform boundary parameters of gait.

Data based segmentation and summarization for sensor data in semiconductor manufacturing

In semiconductor manufacturing processes, sensor data are segmented and summarized in order to reduce storage space. This is conventionally done by segmenting the data based on predefined chamber step information and calculating statistics within the segments. However, segmentation via chamber steps often do not coincide with actual change points in data, which results in suboptimal summarization. This paper proposes a novel framework using abnormal difference and free knot spline with knot removal, to detect actual data change points and summarize on them. Preliminary experiments demonstrate that the proposed algorithm handles arbitrarily shaped data in a robust fashion and shows better performance than chamber step based segmentation and summarization. An evaluation metric based on linearity and parsimony is also proposed.