A mobile cloud computing framework integrating multilevel encoding for performance monitoring in telerehabilitation

Recent years have witnessed a surge in telerehabilitation and remote healthcare systems blessed by the emerging low-cost wearable devices to monitor biological and biokinematic aspects of human beings. Although such telerehabilitation systems utilise cloud computing features and provide automatic biofeedback and performance evaluation, there are demands for overall optimisation to enable these systems to operate with low battery consumption and low computational power and even with weak or no network connections. This paper proposes a novel multilevel data encoding scheme satisfying these requirements in mobile cloud computing applications, particularly in the field of telerehabilitation. We introduce architecture for telerehabilitation platform utilising the proposed encoding scheme integrated with various types of sensors. The platform is usable not only for patients to experience telerehabilitation services but also for therapists to acquire essential support from analysis oriented decision support system (AODSS) for more thorough analysis and making further decisions on treatment

Formations of robotic swarm : an artificial force based approach

Cooperative control of multiple mobile robots is an attractive and challenging problem which has drawn considerable attention in the recent past. This paper introduces a scalable decentralized control algorithm to navigate a group of mobile robots (swarm) into a predefined shape in 2D space. The proposed architecture uses artificial forces to control mobile agents into the shape and spread them inside the shape while avoiding inter-member collisions. The theoretical analysis of the swarm behavior describes the motion of the complete swarm and individual members in relevant situations. We use computer simulated case studies to verify the theoretical assertions and to demonstrate the robustness of the swarm under external disturbances such as death of agents, change of shape etc. Also the performance of the proposed distributed swarm control architecture was investigated in the presence of realistic implementation issues such as localization errors, communication range limitations, boundedness of forces etc.<br /

Two stage architecture for navigating multiple guided weapons into a widespread target

Cooperative control of multiple unmanned vehicles is an attractive and challenging problem which has drawn considerable attention in the recent past. This paper introduces a scalable and decentralized control algorithm for airborne guided weapon system, which aggregates the weapons into a given shape while reaching the surface. The proposed architecture is based on a two stage controller which uses artificial forces to navigate the weapons into the desired geographical area bounded by a simple closed contour and evenly distribute them inside the desired area. The theoretical analysis of the proposed controller describes the motion of the weapon system and derives the conditions for stability and convergence. Moreover, a lower bound for the release height was obtained which guarantees convergence of the complete weapon system into the target area, minimizing collateral damages. The theoretical assertions were verified using computer simulation case studies in which the proposed weapon system was tested under ideal conditions as well as in a realistic scenario. &copy;2008 IEEE

Multiple emitter localization using range only measurements considering geometrical constraints

This paper proposes a constrained optimization approach to improve the accuracy of a Time-of-Arrival (ToA) based multiple target localization system. Instead of using an overdetermined measurement system, this paper uses local distance measurements between the targets/emitters as the geometric constraint.Computer simulations are used to evaluate the performance of the geometrically constrained optimization method

Fusion based 3D tracking of mobile transmitters via robust set-valued state estimation with RSS measurements

This paper investigates the problem of location and velocity detection of a mobile agent using Received Signal Strength (RSS) measurements captured by geographically distributed seed nodes. With inherently nonlinear power measurements, we derive a powerful linear measurement scheme using an analytical measurement conversion technique which can readily be used with RSS measuring sensors. We also employ the concept of sensor fusion in conjunction for the case of redundant measurements to further enhance the estimation accuracy

Energy efficient, fully-connected mesh networks for high speed applications

Fully-connected mesh networks that can potentially be employed in a range of applications, are inherently associated with major deficiencies in interference management and network capacity improvement. The tree-connected (routing based) mesh networks used in today&rsquo;s applications have major deficiencies in routing delays and reconfiguration delays in the implementation stage. This paper introduces a CDMA based fully-connected mesh network, which controls the transmission powers of the nodes in order to ensure that the communication channels remain interference-free and minimizes the energy consumption. Moreover, the bounds for the number of nodes and the spatial configuration are provided to ensures that the communication link satisfies the QoS (Quality of Service) requirements at all times.<br /

An adaptive orientation misalignment calibration method for shoulder movements using inertial sensors : a feasibility study

Qualitative assessment of the progress in physical rehabilitation largely depends on accurate measurement of the range of movements and other kinematic parameters. In clinical practice, wearable inertial sensors have proved to be a potential candidate for such measurements, over the traditional marker based optical systems due to cost and space considerations. The accuracy of wearable sensors have a significant dependence on the initial orientation calibration and the assumption that the sensor will not slip or move with respect to the attached limb. This article introduces a novel calibration algorithm to correct initial orientation misalignment, as well as to track and correct subsequent alignment errors progressively throughout the experiment. The theoretical assertions are validated through controlled experiments with simulated accelerometer and gyroscope measurements

A machine-driven process for human limb length estimation using inertial sensors

The computer based human motion tracking systems are widely used in medicine and sports. The accurate determination of limb lengths is crucial for not only constructing the limb motion trajectories which are used for evaluation process of human kinematics, but also individually recognising human beings. Yet, as the common practice, the limb lengths are measured manually which is inconvenient, time-consuming and requires professional knowledge. In this paper, the estimation process of limb lengths is automated with a novel algorithm calculating curvature using the measurements from inertial sensors. The proposed algorithm was validated with computer simulations and experiments conducted with four healthy subjects. The experiment results show the significantly low root mean squared error percentages such as upper arm - 5.16%, upper limbs - 5.09%, upper leg - 2.56% and lower extremities - 6.64% compared to measured lengths.<br /

BioKin: an ambulatory platform for gait kinematic and feature assessment

A platform to move gait analysis, which is normally restricted to a clinical environment in a well-equipped gait laboratory, into an ambulatory system, potentially in non-clinical settings is introduced. This novel system can provide functional measurements to guide therapeutic interventions for people requiring rehabilitation with limited access to such gait laboratories. BioKin system consists of three layers: a low-cost wearable wireless motion capture sensor, data collection and storage engine, and the motion analysis and visualisation platform. Moreover, a novel limb orientation estimation algorithm is implemented in the motion analysis platform. The performance of the orientation estimation algorithm is validated against the orientation results from a commercial optical motion analysis system and an instrumented treadmill. The study results demonstrate a root-mean-square error less than 4&deg; and a correlation coefficient more than 0.95 when compared with the industry standard system. These results indicate that the proposed motion analysis platform is a potential addition to existing gait laboratories in order to facilitate gait analysis in remote locations

Localization with ghost elimination of emitters via time-delay-of-arrival measurements

This paper investigates the theoretical requirements for unique localization of multiple emitters using time delay of arrival(TDoA) subjected to the data-association problem. Specifically, an examination is carried out to find the necessary fundamental requirements to solve the so-called ghost node problem pertaining to sensor arrays