GRIDDS - A Gait Recognition Image and Depth Dataset

Several approaches based on human gait have been proposed in the literature, either for medical research reasons, smart surveillance, human-machine interaction, or other purposes, whose validation highly depends on the access to common input data through available datasets, enabling a coherent performance comparison. The advent of depth sensors leveraged the emergence of novel approaches and, consequently, the usage of new datasets. In this work we present the GRIDDS - A Gait Recognition Image and Depth Dataset, a new and publicly available gait depth-based dataset that can be used mostly for person and gender recognition purposes. (c) Springer Nature Switzerland AG 2019

Benchmark RGB-D Gait Datasets: A Systematic Review

Human motion analysis has proven to be a great source of information for a wide range of applications. Several approaches for a detailed and accurate motion analysis have been proposed in the literature, as well as an almost proportional number of dedicated datasets. The relatively recent arrival of depth sensors contributed to an increasing interest in this research area and also to the emergence of a new type of motion datasets. This work focuses on a systematic review of publicly available depth-based datasets, encompassing human gait data which is used for person recognition and/or classification purposes. We have conducted this systematic review using the Scopus database. The herein presented survey, which to the best of our knowledge is the first one dedicated to this type of datasets, is intended to inform and aid researchers on the selection of the most suitable datasets to develop, test and compare their algorithms. (c) Springer Nature Switzerland AG 2019

Evaluation of CNN-Based Human Pose Estimation for Body Segment Lengths Assessment

Human pose estimation (HPE) methods based on convolutional neural networks (CNN) have demonstrated significant progress and achieved state-of-the-art results on human pose datasets. In this study, we aimed to assess the perfor-mance of CNN-based HPE methods for measuring anthropometric data. A Vicon motion analysis system as the reference system and a stereo vision system recorded ten asymptomatic subjects standing in front of the stereo vision system in a static posture. Eight HPE methods estimated the 2D poses which were transformed to the 3D poses by using the stereo vision system. Percentage of correct keypoints, 3D error, and absolute error of the body segment lengths are the evaluation measures which were used to assess the results. Percentage of correct keypoints – the stand-ard metric for 2D pose estimation – showed that the HPE methods could estimate the 2D body joints with a minimum accuracy of 99%. Meanwhile, the average 3D error and absolute error for the body segment lengths are 5 cm

Automated functional upper limb evaluation of patients with Friedreich ataxia using serious games rehabilitation exercises.

Friedreich ataxia (FRDA) is a disease with neurological and systemic involvement. Clinical assessment tools commonly used for FRDA become less effective in evaluating decay in patients with advanced FRDA, particularly when they are in a wheelchair. Further motor worsening mainly impairs upper limb function. In this study, we tested if serious games (SG) developed for rehabilitation can be used as an assessment tool for upper limb function even in patients with advanced FRDA.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Lifelong learning with a digital math game: Performance and basic experience differences across age

Gaming is acknowledged as a natural way of learning and established as a mainstream activity. Nevertheless, gaming performance and subjective game experience were hardly examined across adult age groups for which the game was not intended to. In contrast to serious games as specific tools against a natural, age-related decline in cognitive performance, we evaluated performance and subjective experiences of the established math learning game Semideus across three age groups from 19 to 79. Observed decline in performance in terms of processing speed were not exclusively predicted by age, but also by gaming frequency. Strongest age-related drops of processing speed were found for the middle-aged group aged 35 to 59 years. On the other hand, more knowledge-dependent performance measures like the amount of correctly solved problems remained comparably stable. According to subjective ratings, the middle-aged group experienced the game as less fluent and automatic compared to the younger and older groups. Additionally, the elderly group of participants reported fewer negative attitudes towards technology than both younger groups. We conclude that, albeit performance differences with respect to processing speed, subjective gaming experience stayed on an overall high positive level. This further encourages the use of games for learning across age.acceptedVersionPeer reviewe

Can serious games be incorporated with conventional treatment of children with cerebral palsy? A review.

The use of video games in rehabilitation is becoming more popular to clinicians. These games are embedded in off-the-shelf commercial entertainment applications or especially-developed for clinical purposes. Treatment of cerebral palsy (CP) children is a challenging task for clinicians. Lack of motivation and progress monitoring are two important factors clinicians need to deal with. The use of serious games (SG), sometimes referred to as Virtual Rehabilitation (VR), could therefore be an interesting adjuvant to conventional treatment for these patients. This is however a new discipline and many scientific issues remain to be solved. The aim of this paper is to describe available conventional treatment for CP children together with the level of evidence of each approach. A systematic review of the use of SG in rehabilitation is then conducted. 31 papers (7 randomized clinical trials, 16 cohort studies and 8 single-cases studies) were selected and analyzed, and their level of evidence compared to the conventional treatment. These studies reported outcomes for 352 patients. In summary, this review shows that it is difficult to compare those studies despite the large amount of patients. This is due to the lack of standardization in patient rehabilitation strategy and to the use of various clinical scales and scores. This non-standardization in patient follow-up between previously-published works make evidence-based conclusions difficult to obtain in order to support these techniques objectively. The use of SG for rehabilitation purposes currently meets similar issues. This paper proposes standardization strategies in order to improve treatment comparison and SG use in rehabilitation. © 2014 Elsevier Ltd.SCOPUS: re.jinfo:eu-repo/semantics/publishe