Yeh-Liang Hsu

A review of accelerometry-based wearable motion detectors for physical activity monitoring.

Characteristics of physical activity are indicative of one’s mobility level, latent chronic diseases and aging process. Accelerometers have been widely accepted as useful and practical sensors for wearable devices to measure and assess physical activity. This paper reviews the development of wearable accelerometry-based motion detectors. The principle of accelerometry measurement, sensor properties and sensor placements are first introduced. Various research using accelerometry-based wearable motion detectors for physical activity monitoring and assessment, including posture and movement classification, estimation of energy expenditure, fall detection and balance control evaluation, are also reviewed. Finally this paper reviews and compares existing commercial products to provide a comprehensive outlook of current development status and possible emerging technologies.

Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry System

This paper presents the development of a wearable accelerometry system for real-time gait cycle parameter recognition. Using a tri-axial accelerometer, the wearable motion detector is a single waist-mounted device to measure trunk accelerations during walking. Several gait cycle parameters, including cadence, step regularity, stride regularity and step symmetry can be estimated in real-time by using autocorrelation procedure. For validation purposes, five Parkinson’s disease (PD) patients and five young healthy adults were recruited in an experiment. The gait cycle parameters among the two subject groups of different mobility can be quantified and distinguished by the system. Practical considerations and limitations for implementing the autocorrelation procedure in such a real-time system are also discussed. This study can be extended to the future attempts in real-time detection of disabling gaits, such as festinating or freezing of gait in PD patients. Ambulatory rehabilitation, gait assessment and personal telecare for people with gait disorders are also possible applications.

A decision support system for project portfolio selection

Abstract A decision support system (DSS) is developed to help managers select the most appropriate sequences of plans for product research and development (R&D) projects that have strict constraints on budget, time, and resources. The primary objective of the DSS is to provide an optimal combination of R&D projects. The DSS consists of several subsystems, each of which has a specific function. At the core of the DSS are a cost model, which covers time-cost tradeoff analysis, and a strategic selection algorithm, which, based on dynamic programming, provides an optimal development plan for managing R&D projects. A working board supports an interactive environment between managers and the DSS. A data checking system eliminates inconsistent data and plans in advance. This paper identifies key issues in the arrangement of R&D projects and describes various systems that have been interlinked to make the DSS a success. It also reveals that the DSS can be expanded to a decision support system shell to support similar types of problems.

A review of structural shape optimization

Abstract Shape optimization attempts to integrate geometrical modeling, structural analysis, and optimization into one complete and automated computer-aided design process. It determines the shape of the boundary of a two- or three-dimensional structural component of minimum mass under constraints on geometry and structural responses such as stress, displacements and natural frequencies. This paper presents a general review of structural shape optimization, with emphasis on the recent developments in this field. First the general concepts are introduced. Different approaches of the process of shape optimization, which consists of geometrical representation, structural analysis, sensitivity analysis, and optimization algorithms, are reviewed. Then the difficulties in expanding from two-to three-dimensional shape optimization are discussed. Finally the paper concludes that more attention should be paid to research of zero-order optimization algorithms which are better suitable for shape optimization problems, and mechanical design optimization problems in general.

Interpreting results from topology optimization using density contours

Abstract The topology optimization result using material distribution method is a density distribution of the finite elements in the design domain. Interpreting this result has been a major difficulty for integrating topology optimization and shape optimization into an automated structure design procedure. It is also one of the factors that limit the extension of the optimization methods of two-dimensional structures into three-dimensional structures. This paper presents a process for integrating topology optimization and shape optimization. In this process, density contours are used to interpret the topology optimization result, and then further integrate with shape optimization. This is a fully automated procedure, since during this process no human interpretation or intervening is required. This procedure can be extended to the topology and shape optimization of three-dimensional structures. The optimizations of two- and three-dimensional structures are presented in design examples.

Improving thermal properties of industrial safety helmets

Abstract This paper presents the redesign of an industrial safety helmet shell to improve its thermal properties. First an experiment was established to simulate the conditions of a head wearing a helmet. The average temperature beneath the helmet shell, the speed of heat dissipation through convection, and the temperature contour beneath the helmet shell were used to describe the thermal properties of a helmet. Helmets of different types and makes were tested, and various design concepts were examined. Design suggestions for improving thermal properties of industrial safety helmets were made. According to these design suggestions, a new design prototype was developed, tested, and further modified. The thermal properties of our final helmet shell design have improved over the commercially available helmets we tested. It also passed the weight, impact, and penetration tests of the Chinese National Standards. Finally a subjective human evaluation showed that the new helmet design has significantly better thermal properties than existing commercial helmets. Relevance to industry Industrial safety helmets provide head protection for industrial workers. Thermal discomfort is one of the major reasons that industrial workers do not like to wear safety helmets. This paper presents and verifies ways on improving thermal properties of industrial safety helmets.

Developing a fuzzy proportional-derivative controller optimization engine for engineering design optimization problems

In real world engineering design problems, decisions for design modifications are often based on engineering heuristics and knowledge. However, when solving an engineering design optimization problem using a numerical optimization algorithm, the engineering problem is basically viewed as purely mathematical. Design modifications in the iterative optimization process rely on numerical information. Engineering heuristics and knowledge are not utilized at all. In this article, the optimization process is analogous to a closed-loop control system, and a fuzzy proportional–derivative (PD) controller optimization engine is developed for engineering design optimization problems with monotonicity and implicit constraints. Monotonicity between design variables and the objective and constraint functions prevails in engineering design optimization problems. In this research, monotonicity of the design variables and activities of the constraints determined by the theory of monotonicity analysis are modelled in the fuzzy PD controller optimization engine using generic fuzzy rules. The designer only needs to define the initial values and move limits of the design variables to determine the parameters in the fuzzy PD controller optimization engine. In the optimization process using the fuzzy PD controller optimization engine, the function value of each constraint is evaluated once in each iteration. No sensitivity information is required. The fuzzy PD controller optimization engine appears to be robust in the various design examples tested.

A MODULAR MECHATRONIC SYSTEM FOR AUTOMATIC BONE DRILLING

Drilling tools currently used in surgery depends only on the surgeons manual skills to stop the penetration when completing a hole. This paper presents a modular mechatronic system for automatic bone drilling in surgery. The development of a “modular system” that is compatible with motor-driven drills that are commercially available, rather than developing a new surgical drill, is emphasized. A fuzzy controller analyzes the electric current consumed by the DC motor of the drill. When break-through is detected, the power will be cut and stops drilling in order to prevent excessive protrusion of the drill bit. In extensive drilling tests on real human skulls, there were no unexpected failure, and the overshoots of all tests were well less than 2mm.

Development of a portable device for telemonitoring of snoring and obstructive sleep apnea syndrome symptoms.

The First Intensive Balkan Telemedicine and e-Health Seminar was held in the war-ravaged capital of Kosova, Prishtina, in 2002. This event was created under the auspices of the International Virtual e Hospital (IVeH). This organization, the brain child of Rifat Latifi, M.D., was established with the intent to establish a medical capability using telemedicine in an environment where the health infrastructure had been totally destroyed by war. Recently, the IVeH opened six regional telemedicine centers in Kosova. These centers are in the cities of Gjilan, Prizren, Gjakove, Peja, Skenderaj, and Mitrovica. These centers cover the entire country through a telemedicine network. Recently, the Second Intensive Seminar was organized and held October 2123, 2007, in Tirana, Albania. It was organized to broaden the concept of telemedicine and e-health in the Balkans region, and to introduce telemedicine in Albania, which was an ideal choice for holding the seminar. The seminar represented a significant step for Albania as it embraces the concept of telemedicine. These important events have shaped telemedicine development in the Balkans and are serving as a model for the rest of the South Eastern European countries to embrace telemedicine and e-health. This paper summarizes the events of this second seminar and addresses the importance telemedicine has for the region.

A sequential approximation method using neural networks for engineering design optimization problems

There are three characteristics in engineering design optimization problems: (1) the design variables are often discrete physical quantities; (2) the constraint functions often cannot be expressed analytically in terms of design variables; (3) in many engineering design applications, critical constraints are often ‘pass–fail’, ‘0–1’ type binary constraints. This paper presents a sequential approximation method specifically for engineering optimization problems with the three characteristics. In this method a back-propagation neural network is trained to simulate a rough map of the feasible domain formed by the constraints using a few representative training data. A training data point consists of a discrete design point and whether this design point is feasible or infeasible. Function values of the constraints are not required. A search algorithm then searches for the optimal point in the feasible domain simulated by the neural network. This new design point is checked against the true constraints to see whether it is feasible, and is then added to the training set. The neural network is trained again with this added information, in the hope that the network will better simulate the boundary of the feasible domain of the true optimization problem. Then a further search is made for the optimal point in this new approximated feasible domain. This process continues in an iterative manner until the approximate model locates the same optimal point in consecutive iterations. A restart strategy is also employed so that the method may have a better chance to reach a global optimum. Design examples with large discrete design spaces and implicit constraints are solved to demonstrate the practicality of this method.