Exergames have the potential to be used as physical-cognitive training tools. Although numerous studies investigated the physical and motivational effects of Exergaming, a comprehensive summary of training effects in healthy adults is still missing. This scoping review aims to identify available evidence and research gaps on absolute and relative effects of Exergame training on physical indicators (effectiveness) and motivation (attractiveness) compared to no or conventional training in healthy adults. A systematic literature search was performed in EBSCOhost, WoS CC, SURF, and Science Research for studies meeting the following criteria: a) randomized controlled trials with Exergames compared to conventional training and/ or no treatment; b) healthy adults (age: 18 to 64 years); c) Exergame training interventions; d) assessment of pre-post differences, primary outcomes: endurance, strength, flexibility, speed, balance, sensorimotor coordination, sports skills, player experience; secondary outcomes: adverse events, physical activity level, attitudes, and knowledge. Methodological quality of included studies was assessed using the PEDro Scale. Charted data were categorized according to the PICOS framework. Mean differences, 95% confidence intervals, and effect sizes (ES) were calculated for continuous outcomes. Evidence Maps were created to illustrate the estimated Risk of Bias, estimated effect, and sample sizes. Eighteen publications with 907 participants were included. The number of studies per outcome was low (2 to 9balance:). Studies on coordination and knowledge were lacking. No study analyzed the relative effects of speed training with Exergames. Absolute effects of Exergame training ranged from no to large effects. Significant ES were consistently found for skill training. Negative effects were found for individual parameters. Relative effects of Exergame training ranged from no to large effects (one exception). A moderate absolute effect favoring traditional training was found for skill training. The remaining results suggest that Exergaming elicited similar training effects compared to conventional training. A high variance of applied training, corresponding training parameters (FITT-VP), outcome measures, as well as methodological deficits and incomplete reporting were identified in included studies. Therefore, a lack of high-quality studies and reviews was identified. Future research should conduct high quality RCT studies analyzing the effectiveness and attractiveness in Exergames. In addition, more suitable, well-designed Exergames should be developed.

Exergames have the potential to be used as motivating physical training tools. Up to date, there are numerous studies and reviews available that focus on specific training effects. However, a comprehensive summary of conditioning, coordinative and sports skill related training effects in healthy adults is still missing. This contribution presents the protocol for an overview of reviews (Pollock et al. 2021) including the results of an initial literature research. Aim of the overview was to: a) summarize absolute and relative effects of training with Exergames compared to no or conventional training; b) identify possible mediators for varying training responses; c) identify gaps in the current evidence. The performed literature research resulted in only five publications meeting the eligibility criteria. This confirms the lack of and need for systematic reviews that summarize the existing research regarding the effects of Exergames in healthy adults.

Exergames have the potential to be used as motivating physical training tools. Numerous studies are currently available that investigate the effects of physical training with Exergames. However, most studies focus on specific training effects or specific target groups. A comprehensive summary of conditioning, coordinative and sports skill related training effects with Exergames in healthy adults is still missing. This contribution presents the protocol for a systematic review that aims to: a) summarize absolute and relative effects of training with Exergames on physical indicators and motivation compared to no or conventional training; b) identify possible mediators and moderators for varying training responses; c) identify gaps in the current evidence related to Exergame-based training.

Appears in: EDULEARN20 Proceedings Publication year: 2020Pages: 5882-5888ISBN: 978-84-09-17979-4ISSN: 2340-1117doi: 10.21125/edulearn.2020.1531Conference name: 12th International Conference on Education and New Learning TechnologiesDates: 6-7 July, 2020Location: Online Conference

Serious games are digital games that have an additional goal beyond entertainment. Recently, many studies have explored different quality criteria for serious games, including effectiveness and attractiveness. Unfortunately, the double mission of serious games, that is, simultaneous achievement of intended effects (serious part) and entertainment (game part), is not adequately considered in these studies. This paper aims to identify essential quality criteria for serious games. The fundamental goal of our research is to identify important factors of serious games and to adapt the existing principles and requirements from game-related literature to effective and attractive serious games. In addition to the review of the relevant literature, we also include workshop results. Furthermore, we analyzed and summarized 22 state-of-the-art serious games for education and health. The selected best-practice serious games either prove their effectiveness through scientific studies or by winning game awards. For the analysis of these games, we refer to “DIN SPEC 91380 Serious Games Metadata Format.” A summarized text states quality criteria for both the serious and the game part, and especially the balance between them. We provide guidelines for high-quality serious games drawn from literature analysis and in close cooperation with domain experts.

Modeling and predicting load courses and HR responses enables individually optimal training control. In HR controlled endurance training, load is expected to gradually decrease to keep HR levels constant due to cardiac drift. This paper analyzes if gender, time under load or progress of training influences characteristics of load controlled by HR in continuous exercise during a long-term training intervention. Nine healthy adults performed a twelve-week training intervention on a bike ergometer. During the Intensive Continuous Method, load was automatically adjusted (ALC) to keep individual HR in the range of 75

The use of wearable devices or "wearables" in the physical activity domain has been increasing in the last years. These devices are used as training tools providing the user with detailed information about individual physiological responses and feedback to the physical training process. Advantages in sensor technology, miniaturization, energy consumption and processing power increased the usability of these wearables. Furthermore, available sensor technologies must be reliable, valid and usable. Considering the variety of the existing sensors not all of them are suitable to be integrated in wearables. The application and development of wearables has to consider the characteristics of the physical training process to improve the effectiveness and efficiency as training tools. During physical training, it is essential to elicit individual optimal strain to evoke the desired adjustments to training. One important goal is to neither overstrain nor under challenge the user. Many wearables use heart rate as indicator for this individual strain. However, due to a variety of internal and external influencing factors, heart rate kinetics are highly variable making it difficult to control the stress eliciting individually optimal strain. For optimal training control it is essential to model and predict individual responses and adapt the external stress if necessary. Basis for this modeling is the valid and reliable recording of these individual responses. Depending on the heart rate kinetics and the obtained physiological data, different models and techniques are available that can be used for strain or training control. Aim of this review is to give an overview of measurement, prediction, and control of individual heart rate responses. Therefore, available sensor technologies measuring the individual heart rate responses are analyzed and approaches to model and predict these individual responses discussed. Additionally, the feasibility for wearables is analyzed.

Aim of the study was to identify possible predictors influencing the variability of individual short-term heart rate (HR) responses to submaximal interval exercise using a probabilistic model. Short-term HR responses to the change of load bouts obtained in a twelve-week training intervention were analyzed. Questionnaires gathered preceding sport activity, sleep, nutrition, health and mood prior to each training session. Additionally, time of the day and number of interval was included in calculation. Multiple regression method was used to identify predictors for start heart rate (HR), steady state HR, and for the slope of the HR curve. Especially the number of the interval, physical and mental health, and negative mood were influencing these responses. The start heart rate was identified as predictor in five of eight response parameter. Time was a factor highly varying between participants. Future research need to validate the results in a wider sample and integrate more parameters in the analysis.

Aim of this study was to test whether a monoexponential formula is appropriate to analyze and predict individual responses to the change of load bouts online during training. Therefore, 234 heart rate (HR) data sets obtained from extensive interval protocols of four participants during a twelve-week training intervention on a bike ergometer were analyzed. First, HR for each interval was approximated using a monoexponential formula. HR at onset of exercise (HR start ), HR induced by load (HR steady ) and the slope of HR (c) were analyzed. Furthermore, a calculation routine incrementally predicted HR steady using measured HR data after onset of exercise. Validity of original and approximated data sets were very high (r² =0.962, SD =0.025; Max =0.991, Min =0.702). HR start was significantly different between all participants (one exception). HR steady was similar in all participants. Parameter c was independent of the duration of intervention and intervals regarding one training session but was significantly different in all participants (one exception). Final HR was correctly predicted on average after 58.8 s (SD = 34.77, Max =150 s, Min =30 s) based on a difference criteria of less than 5 bpm. In 3 participants, HR steady was predicted correctly in 142 out of 175 courses (81.1%).

Setting an appropriate training load is one of the key elements for the success of exergames. Especially for the cardiovascular training, the adaptation of the current training load in accordance to an individually predetermined target training load plays an important role. In this paper, a new approach for the estimation and prediction of an individual's heart rate based on a monoexponential formula is presented and evaluated using statistical data. The estimation and prediction of the heart rate is a key factor for the calculation of adequate exertion parameters and therefore for the adaptation and personalization of exertion games, i.e. games that use whole-body exercises for game control. The tests reveal that the course of the heart rate response to changes of load bouts is not stable. Only a differential influence of gender on the HR course depending on the particular load bout can be found.

OBJECTIVEThis article presents a feasibility study of using an algorithm for an individual and adaptive control of training load in an ergometer-controlled exergame for aerobic training. An additional goal was to investigate the effects of the adaptive game on the players' motivation.MATERIALS AND METHODSA two-phase approach (calibration and exercise phase) was applied in a sample of 16 physically active adults. In the cardio-exergame "LetterBird," the flight of a pigeon was controlled by the pedaling rate of a bike ergometer as input device. During the calibration phase the individual heart rate (HR) responses of the players were measured. In the exercise phase, these data were used to adjust the resistance of the ergometer using the proposed algorithm. The purpose of this algorithm was to induce an individually defined target HR and to keep it in a steady state. In order to establish a reference for further studies, the game experience was measured using the kids-Game Experience Questionnaire.RESULTSIn 15 of 16 participants the actual HR reached the intended individual HR range within 10 minutes after onset of exercise. However, the induced HR initially exceeded the target HR in 13 participants, which made load adjustments necessary. The analysis of the kids-Game Experience Questionnaire confirmed the motivational effect of the exergame "LetterBird."CONCLUSIONSThe results confirm that the proposed algorithm for personalized HR control in the game "LetterBird" is feasible. Furthermore, the cardio-exergame "LetterBird" seems to have a substantial short-term motivating effect.

The following paper addresses the development and first tests of an algorithm for individual control of physical load in Serious Games for Sports and Health. The purpose is to monitor and control the heart rate (HR) as an individual indicator of optimal training load. In the context of the Serious Game "LetterBird", developed by KOM, a playful and yet effective physical training can be realized. In this game the flight of a pidgeon is controlled by a cycle ergometer. The goal is to collect letters approaching the bird at different altitudes. From the perspective of computer science in sport, the aim was to generate an algorithm that approaches and maintains a defined target HR effectively and efficiently in individuals with different properties (e.g., age, sex, performance and health level) within the game. For an initial application and testing of this algorithm, a two-part test series was performed with 4 participants. The results are promising: The intended HR could be evoked in all participants. Yet further tests need to be done to improve the adaptations.

The following paper addresses the development and first tests of an algorithm for individual control of physical load in Serious Games for Sports and Health. The purpose is to monitor and control the heart rate (HR) as an individual indicator of optimal training load. In the context of the Serious Game "LetterBird", developed by KOM, a playful and yet effective physical training can be realized. In this game the flight of a pidgeon is controlled by a cycle ergometer. The goal is to collect letters approaching the bird at different altitudes.From the perspective of computer science in sport, the aim was to generate an algorithm that approaches and maintains a defined target HR effectively and efficiently in individuals with different properties (e.g., age, sex, performance and health level) within the game.For an initial application and testing of this algorithm, a two-part test series was performed with 4 participants. The results are promising: The intended HR could be evoked in all participants. Yet further tests need to be done to improve the adaptations.