Rhythmic skills are natural and widespread in the general population. The majority can track the beat of music and move along with it. These abilities are meaningful from a cognitive standpoint given their tight links with prominent motor and cognitive functions such as language and memory. When rhythmic skills are challenged by brain damage or neurodevelopmental disorders, remediation strategies based on rhythm can be considered. For example, rhythmic training can be used to improve motor performance (e.g., gait) as well as cognitive and language skills. Here, we review the games readily available in the market and assess whether they are well-suited for rhythmic training. Games that train rhythm skills may serve as useful tools for retraining motor and cognitive functions in patients with motor or neurodevelopmental disorders (e.g., Parkinson’s disease, dyslexia, or ADHD). Our criteria were the peripheral used to capture and record the response, the type of response and the output measure. None of the existing games provides sufficient temporal precision in stimulus presentation and/or data acquisition. In addition, games do not train selectively rhythmic skills. Hence, the available music games, in their present form, are not satisfying for training rhythmic skills. Yet, some features such as the device used, the interface or the game scenario provide good indications for devising efficient training protocols. Guidelines are provided for devising serious music games targeting rhythmic training in the future.

Rhythm perception and production can be disrupted by neurological or neurodevelopmental disorders (e.g., Parkinson's disease, dyslexia). Rhythm deficits are associated with poor performance in language, attention, and working memory tasks. Retraining rhythmic skills may thus provide a promising avenue for improving these associated cognitive functions. To this end, here we present a new protocol for selective training of rhythmic skills implemented in a tablet serious game called Rhythm Workers. Experiment 1 served to select 54 musical excerpts based on the tapping performance of 18 nonmusicians who moved to the beat of music. The excerpts were sorted in terms of the difficulty of tracking their beat, and assigned to different difficulty levels in the game. In Experiment 2, the training protocol was devised and tested in a proofof-concept study, including two versions of the game. One version (tapping version) required a synchronized motor response (via tapping), while the other (perception version) asked for a perceptual judgment. Ten participants were trained with one version and 10 with the other version of Rhythm Workers, for 2 weeks. A control group (n ¼ 10) did not receive any training. Participants in the experimental groups showed high compliance and motivation in playing the game. The effect of the training on rhythm skills yielded encouraging results with both versions of the game. Rhythm Workers thus appears to be a motivating and potentially efficient way to train rhythmic abilities in healthy young adults, with possible applications for (re)training these skills in individuals with rhythm disorders.

This work proposes to improve the accuracy of joint angle estimates obtained from an RGB-D sensor. It is based on a constrained extended Kalman Filter that tracks inputted measured joint centers. Since the proposed approach uses a biomechanical model, it allows physically consistent constrained joint angles and constant segment lengths to be obtained. A practical method that is not sensor-specific for the optimal tuning of the extended Kalman filter covariance matrices is provided. It uses reference data obtained from a stereophotogrammetric system but it has to be tuned only once since it is task-specific only. The improvement of the optimal tuning over classical methods in setting the covariance matrices is shown with a statistical parametric mapping analysis. The proposed approach was tested with six healthy subjects who performed four rehabilitation tasks. The accuracy of joint angle estimates was assessed with a reference stereophotogrammetric system. Even if some joint angles, such as the internal/external rotations, were not well estimated, the proposed optimized algorithm reached a satisfactory average root mean square difference of 9.7 ∘ and a correlation coefficient of 0.8 for all joints. Our results show that an affordable RGB-D sensor can be used for simple in-home rehabilitation when using a constrained biomechanical model.

The advancement of motion sensing input devices has enabled the collection of multivariate time-series body movement data. Analyzing such type of data is challenging due to the large amount of data and the task of mining for interesting temporal movement patterns. To address this problem, we propose an interface to visualize and analyze body movement data. This visualization enables users to navigate and explore the evolution of movement over time for different movement areas. We also propose a clustering method based on hierarchical clustering to group similar movement patterns. The proposed visualization is illustrated with a case study which demonstrates the ability of the interface to analyze body movements.

Last years have seen a growing interest on the Serious Games topic-and in particular on Games for Health-from both scientific and industrial communities. However not only the effectiveness of this kind of games is not yet demonstrated but the distribution and adoption of these games from the normal public is still very low. In this paper we present a design strategy we adopted in on the occasion of the development of a game for hemiplegic rehabilitation named "Hammer and Planks". This game strategy allowed us to create a "game for all", as will be demonstrated by the example of the usage of the game on the occasion of a game event in the south of France.