A quantifiable kinematic characterisation of hand function

The thesis is to develop a novel method for hand functional assessment. The study confirmed the reachable space concept is better than the joint angles to describe the range of motion of the hand. The research discovers an efficient method to determine the perimeter and capacity of the reachable space

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

Describing human finger flexibility via reachable subspaces

In recent years, the reachable space concept has attracted the attention of many researchers as a mean of describing finger flexibility. Existing approaches such as exhaustive scanning or Monte Carlo methods to obtain the reachable space are resource-hungry techniques. In this paper, we introduce a novel approach to determine and quantify the reachable space of the finger. The approach was developed around a set of formulae determining the boundary of the reachable space. The Monte Carlo simulation is proposed to estimate the capacity of the reachable space. Using the new technique, reachable spaces can be visualised and quantified in order to effectively compare the functionality of different subjects and their therapeutic status. The performance of the proposed method was evaluated against the kinematic feed-forward approach. The computational cost to obtain the reachable space is significantly less than the standard kinematic feed-forward approach due to exclusive description of the reachable space boundary, unique to the proposed approach

Quantifying the human finger reachable space

Describing the flexibility of the hand using the reachable space concept has drawn the attention of many researchers in recent years. Existing approaches involving numerical techniques to obtain the reachable space are generally computationally expensive. In this study, we propose a resource-friendly approach to determine and quantify the bidimensional reachable space of the finger. The fundamental idea of the approach connects to a set of arc formulae for the boundary of the reachable space. These formulae of the boundary result a unique description to calculate the area of the reachable space using Green\u27s theorem. Adopting this novel approach, reachable spaces can be visualised and quantified to effectively evaluate the functionality of different subjects and their therapeutic conditions. We evaluated the performance of the proposed approach against the popular kinematic feedforward approach and Monte Carlo simulation separately. The exclusive description of the reachable space boundary resulted in significant improvement to the execution time while delivering more accurate quantification values

Measurement and assessment of hand functionality via a cloud-based implementation

This book constitutes the proceedings of the 13th International Conference on Smart Homes and Health Telematics, ICOST 2015, held in Geneva, Switzerland, in June 2015

Deducing the reachable space from fingertip positions

The reachable space of the hand has received significant interests in the past from relevant medical researchers and health professionals. The reachable space was often computed from the joint angles acquired from a motion capture system such as gloves or markers attached to each bone of the finger. However, the contact between the hand and device can cause difficulties particularly for hand with injuries, burns or experiencing certain dermatological conditions. This paper introduces an approach to find the reachable space of the hand in a non-contact measurement form utilizing the Leap Motion Controller. The approach is based on the analysis of each position in the motion path of the fingertip acquired by the Leap Motion Controller. For each position of the fingertip, the inverse kinematic problem was solved under the physiological multiple constraints of the human hand to find a set of all possible configurations of three finger joints. Subsequently, all the sets are unified to form a set of all possible configurations specific for that motion. Finally, a reachable space is computed from the configuration corresponding to the complete extension and the complete flexion of the finger joint angles in this set

3D motion matching algorithm using signature feature descriptor

This paper introduces a basic frame for rehabilitation motion practice system which detects 3D motion trajectory with the Microsoft Kinect (MSK) sensor system and proposes a cost-effective 3D motion matching algorithm. The rehabilitation motion practice system displays a reference 3D motion in the database system that the player (patient) tries to follow. The player’s motion is traced by the MSK sensor system and then compared with the reference motion to evaluate how well the player follows the reference motion. In this system, 3D motion matching algorithm is a key feature for accurate evaluation for player’s performance. Even though similarity measurement of 3D trajectories is one of the most important tasks in 3D motion analysis, existing methods are still limited. Recent researches focus on the full length 3D trajectory data set. However, it is not true that every point on the trajectory plays the same role and has the same meaning. In this situation, we developed a new cost-effective method that only uses the less number of features called ‘signature’ which is a flexible descriptor computed from the region of ‘elbow points’. Therefore, our proposed method runs faster than other methods which use the full length trajectory information. The similarity of trajectories is measured based on the signature using an alignment method such as dynamic time warping (DTW), continuous dynamic time warping (CDTW) or longest common sub-sequence (LCSS) method. In the experimental studies, we applied the MSK sensor system to detect, trace and match the 3D motion of human body. This application was assumed as a system for guiding a rehabilitation practice which can evaluate how well the motion practice was performed based on comparison of the patient’s practice motion traced by the MSK system with the pre-defined reference motion in a database. In order to evaluate the accuracy of our 3D motion matching algorithm, we compared our method with two other methods using Australian sign word dataset. As a result, our matching algorithm outperforms in matching 3D motion, and it can be exploited for a base framework for various 3D motion-based applications at low cost with high accuracy

Towards Developing Dialogue Systems with Entertaining Conversations

This paper explores a novel approach to developing a dialogue system that is able to make entertaining conversations with users. It proposes a method to improve the current goal-driven dialogue systems which supportusers for specific tasks while satisfying users’goals with entertaining conversations. It then develops a dialoguesystem in which a set of features are considered to generate entertaining conversations, while reasonably prolonging the original too short dialogue. The game refinement measure is employed for the assessment of attractiveness since the conversations in dialogue systems can be seen as the process by which a player creates shoots or moves to win a game. The dialogues generated by the proposed method are evaluated by human subjects. The results confirm the effectiveness of the proposed method. The present idea can be a promising way to realize dialogue systems with entertaining conversations although further investigations are needed