Optimization Algorithms for Integrating Advanced Facility-Level Healthcare Technologies into Personal Healthcare Devices

Healthcare is one of the most important services to preserve the quality of our daily lives, and it is capable of dealing with issues such as global aging, increase in the healthcare cost, and changes to the medical paradigm, i.e., from the in-facility cure to the prevention and cure outside the facility. Accordingly, there has been growing interest in the smart and personalized healthcare systems to diagnose and care themselves. Such systems are capable of providing facility-level diagnosis services by using smart devices (e.g., smartphones, smart watches, and smart glasses). However, in realizing the smart healthcare systems, it is very difficult, albeit impossible, to directly integrate high-precision healthcare technologies or scientific theories into the smart devices due to the stringent limitations in the computing power and battery lifetime, as well as environmental constraints. In this dissertation, we propose three optimization methods in the field of cell counting systems and gait-aid systems for Parkinson's disease patients that address the problems that arise when integrating a specialized healthcare system used in the facilities into mobile or wearable devices. First, we present an optimized cell counting algorithm based on heuristic optimization, which is a key building block for realizing the mobile point-of-care platforms. Second, we develop a learning-based cell counting algorithm that guarantees high performance and efficiency despite the existence of blurry cells due to out-focus and varying brightness of background caused by the limitation of lenses free in-line holographic apparatus. Finally, we propose smart gait-aid glasses for Parkinson’s disease patients based on mathematical optimization. ⓒ 2017 DGISTopenI. Introduction 1-- 1.1 Global Healthcare Trends 1-- 1.2 Smart Healthcare System 2-- 1.3 Benefits of Smart Healthcare System 3-- 1.4 Challenges of Smart Healthcare. 4-- 1.5 Optimization 6-- 1.6 Aims of the Dissertation 7-- 1.7 Dissertation Organization 8-- II.Optimization of a cell counting algorithm for mobile point-of-care testing platforms 9-- 2.1 Introduction 9-- 2.2 Materials and Methods. 13-- 2.2.1 Experimental Setup. 13-- 2.2.2 Overview of Cell Counting. 16-- 2.2.3 Cell Library Optimization. 18-- 2.2.4 NCC Approximation. 20-- 2.3 Results 21-- 2.3.1 Cell Library Optimization. 21-- 2.3.2 NCC Approximation. 23-- 2.3.3 Measurement Using an Android Device. 28-- 2.4 Summary 32-- III.Human-level Blood Cell Counting System using NCC-Deep learning algorithm on Lens-free Shadow Image. 33-- 3.1 Introduction 33-- 3.2 Cell Counting Architecture 36-- 3.3 Methods 37-- 3.3.1 Candidate Point Selection based on NCC. 37-- 3.3.2 Reliable Cell Counting using CNN. 40-- 3.4 Results 43-- 3.4.1 Subjects . 43-- 3.4.2 Evaluation for the cropped cell image 44-- 3.4.3 Evaluation on the blood sample image 46-- 3.4.4 Elapsed-time evaluation 50-- 3.5 Summary 50-- IV.Smart Gait-Aid Glasses for Parkinson’s Disease Patients 52-- 4.1 Introduction 52-- 4.2 Related Works 54-- 4.2.1 Existing FOG Detection Methods 54-- 4.2.2 Existing Gait-Aid Systems 56-- 4.3 Methods 57-- 4.3.1 Movement Recognition. 59-- 4.3.2 FOG Detection On Glasses. 62-- 4.3.3 Generation of Visual Patterns 66-- 4.4 Experiments . 67-- 4.5 Results 69-- 4.5.1 FOG Detection Performance. 69-- 4.5.2 Gait-Aid Performance. 71-- 4.6 Summary 73-- V. Conclusion 75-- Reference 77-- 요약문 89본 논문은 의료 관련 연구시설 및 병원 그리고 실험실 레벨에서 사용되는 전문적인 헬스케어 시스템을 개인의 일상생활 속에서 사용할 수 있는 스마트 헬스케어 시스템에 적용시키기 위한 최적화 문제에 대해 다룬다. 현대 사회에서 의료비용 증가 세계적인 고령화에 따라 의료 패러다임은 질병이 발생한 뒤 시설 내에서 치료 받는 방식에서 질병이나 건강관리에 관심있는 환자 혹은 일반인이 휴대할 수 있는 개인용 디바이스를 이용하여 의료 서비스에 접근하고, 이를 이용하여 질병을 미리 예방하는 방식으로 바뀌었다. 이에 따라 언제, 어디서나 스마트 디바이스(스마트폰, 스마트워치, 스마트안경 등)를 이용하여 병원 수준의 예방 및 진단을 실현하는 스마트 헬스케어가 주목 받고 있다. 하지만, 스마트 헬스케어 서비스 실현을 위하여 기존의 전문 헬스케어 장치 및 과학적 이론을 스마트 디바이스에 접목하는 데에는 스마트 디바이스의 제한적인 컴퓨팅 파워와 배터리, 그리고 연구소나 실험실에서 발생하지 않았던 환경적인 제약조건으로 인해 적용 할 수 없는 문제가 있다. 따라서 사용 환경에 맞춰 동작 가능하도록 최적화가 필요하다. 본 논문에서는 Cell counting 분야와 파킨슨 환자의 보행 보조 분야에서 전문 헬스케어 시스템을 스마트 헬스케어에 접목시키는데 발생하는 세 가지 문제를 제시하고 문제 해결을 위한 세 가지 최적화 알고리즘(Heuristic optimization, Learning-based optimization, Mathematical optimization) 및 이를 기반으로 하는 시스템을 제안한다.DoctordCollectio

Context-awareness for mobile sensing: a survey and future directions

The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions

MilkGuard: Predictive Modeling and Mobile App Development for Affordable, Usable Breast Milk Diagnostic

Breast milk is considered the gold standard of infant nutrition, but some infants around the world lack access to it due to maternal health complications or other considerations. Human breast milk banks do exist to try to alleviate this problem, but most are underfunded and have high operational costs, making it difficult for some infants to obtain safe, reliable donated breast milk. Existing methods of testing breast milk are expensive, so the MilkGuard project was conceptualized in 2017 as a fast, economical, and highly usable bacterial contamination detection system. Prior to this year, previous MilkGuard teams had developed a system that was faster and more affordable than prior methods, but its main drawbacks were that it was difficult to use and that it lacked the sensitivity to detect low Escherichia coli (E. coli) contamination levels. To ameliorate these drawbacks, our goals for this year were 1) to improve MilkGuard’s sensitivity to the Human Milk Banking Association of North America’s (HMBANA) lower limit of detection standard of 104 CFU/mL, 2) to increase the ease of the assay process, and 3) to achieve these objectives in an economical and environmentally-friendly way. Through COMSOL Multiphysics software simulations, we proved the possibility of realistically optimizing biosensor parameters on a computer. Since the simulations were virtual, we discovered an optimal biosensor configuration without the need to purchase, manufacture, and test hundreds of physical sensors. Future teams can quickly confirm these results by building a physical sensor in the lab. We also developed the MilkGuard app, which greatly simplifies the colorimetric analysis process for the user. This mobile app uses our improved color-analysis algorithm which improves detection sensitivity around the HMBANA’s lowered limit of detection standard, given the same image data to analyze. The efficacy of our new color analysis algorithm can be confirmed by future teams in the lab, and our current regression curve can be made more robust with a larger sample size. Taken together, our developments this year have increased the usability and sensitivity of the MilkGuard system, which can improve bacterial contamination testing by milk banks and move one step closer to equitable access to safe breast milk for infants around the world

GUARDIANS final report

Emergencies in industrial warehouses are a major concern for firefghters. The large dimensions together with the development of dense smoke that drastically reduces visibility, represent major challenges. The Guardians robot swarm is designed to assist fire fighters in searching a large warehouse. In this report we discuss the technology developed for a swarm of robots searching and assisting fire fighters. We explain the swarming algorithms which provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also one of the means to locate the robots and humans. Thus the robot swarm is able to locate itself and provide guidance information to the humans. Together with the re ghters we explored how the robot swarm should feed information back to the human fire fighter. We have designed and experimented with interfaces for presenting swarm based information to human beings

Dagstuhl Reports : Volume 1, Issue 2, February 2011

Online Privacy: Towards Informational Self-Determination on the Internet (Dagstuhl Perspectives Workshop 11061) : Simone Fischer-Hübner, Chris Hoofnagle, Kai Rannenberg, Michael Waidner, Ioannis Krontiris and Michael Marhöfer Self-Repairing Programs (Dagstuhl Seminar 11062) : Mauro Pezzé, Martin C. Rinard, Westley Weimer and Andreas Zeller Theory and Applications of Graph Searching Problems (Dagstuhl Seminar 11071) : Fedor V. Fomin, Pierre Fraigniaud, Stephan Kreutzer and Dimitrios M. Thilikos Combinatorial and Algorithmic Aspects of Sequence Processing (Dagstuhl Seminar 11081) : Maxime Crochemore, Lila Kari, Mehryar Mohri and Dirk Nowotka Packing and Scheduling Algorithms for Information and Communication Services (Dagstuhl Seminar 11091) Klaus Jansen, Claire Mathieu, Hadas Shachnai and Neal E. Youn