Computerized Cognitive games versus Cognitive Exergame: The comparison of motor and cognitive functions enhancement in late-adulthood

doi:10.21203/rs.3.rs-4849606/v1

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Computerized Cognitive games versus Cognitive Exergame: The comparison of motor and cognitive functions enhancement in late-adulthood

https://doi.org/10.21203/rs.3.rs-4849606/v1

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Background

Considering the importance of cognitive and motor functions of individuals in their late-adulthood, the present study was conducted to evaluate the effectiveness of a cognitive exergame, called Neurolight compared to computerized cognitive games, in enhancing core executive functions and motor performance at the end of adulthood and early old age.

Methods

A total of 36 individuals in the age range of 60 to 69 years were studied in the form of three groups: cognitive-motor exergame group using Neurolight, Computerized cognitive games group using Maghzineh, and control group.

Results

The results showed that cognitive-motor exercises using Neurolight, for 24 sessions, were able to significantly improve working memory, inhibitory control, and balance in individuals in this age group.

Conclusion

This finding supports the other studies suggesting combined cognitive and physical exercises for better effect. Based on its findings, the use of this exercise system can be suggested to coaches and therapists working with the elderly.

Neurolight

Physical-Cognitive Training

Executive Functions

Aging

With the passage of time and the onset of the aging process, negative changes occur in various dimensions of elderly individuals' functioning. It has been shown that with aging, motor functions gradually decline, which reduces the quality of life due to the crucial role of motor functions [1]. On the other hand, one important aspect that may experience a decline as a result of aging is cognitive function [2]. These functions are related to information processing, thinking, and decision-making processes and play a crucial role in improving individuals' lives [3]. Studies have shown that in the third and fourth decades of life, the volume of brain tissue in the frontal, temporal, and parietal lobes decreases, which may be the cause of declining performance in a wide range of cognitive processes such as memory, decision-making, and selective attention in later decades of life [4]. In the field of preventing decline in cognitive and physical functioning during aging, there are various protocols, including physical exercise, cognitive games, nutrition, and neuro-psycho-interventions such as brain stimulation [5]. Some of these interventions, such as physical activity, which are related to lifestyle changes, have more preventive and performance-enhancing aspects in healthy individuals and have received considerable attention from researchers in recent decades [6]. Regular physical activity is one of the influential factors that can reduce the rate of age-related decline and enhance performance. Regular physical activity promotes and maintains individuals' health [7]. Regular physical activity improves both physical and mental health and can significantly affect elements such as self-esteem, self-efficacy, body image, and mood [8]. Despite many achievements of physical activity, it is surprising that the majority of older adults experience more inactivity during retirement and old age [9].

In order to prevent cognitive decline during aging, physical and cognitive training are interventions that are prominent in the research literature [10]. Computer-based cognitive training programs have been well received by many therapists due to their non-invasiveness, safety, and ease of implementation. Various research studies on the effectiveness of these types of exercises in cognitive rehabilitation of individuals with disorders and cognitive enhancement in healthy individuals are still ongoing [11]. Furthermore, research has also shown that physical exercises may slow down or reverse age-related cognitive decline [12]. In other words, it seems that physical exercises may directly impact cognitive performance. There are multiple mechanisms regarding the relationship between physical activity and cognitive function. Firstly, physical exercises engage similar areas of the brain that are also used for controlling higher cognitive processes [13]. Additionally, physical exercises can improve cognitive functions by secreting certain substances such as serotonin, dopamine, and brain-derived neurotrophic factor (BDNF) as a result of exercise [14]. Besides the direct effects that physical activity can have on cognitive functions, these exercises can have compounded benefits by improving older adults’ ability to perform daily tasks, thus preventing cognitive decline and improving individuals’ quality of life [15]. Despite the beneficial effects that cognitive and physical exercises can have individually in preventing cognitive decline in old age, recent research has shown that combining these exercises is more effective than doing each one alone [16]. On the other hand, many cognitive activities that humans engage in throughout the day are not performed in a laboratory setting but rather in real-life situations where individuals are required to make decisions or react while being physically active. Therefore, combining physical and cognitive activities can make them more relevant to real-life conditions [10]. This concept can be viewed from the perspective of transferability in the effectiveness of cognitive exercises, where transfer refers to the effectiveness of cognitive exercises in real-life situations [17]. Based on this, the effects of cognitive exercises alongside physical exercises can be synergistic and enhance each other's effects [18]. This occurs when the effects of physical activity and cognitive tasks complement each other [19]. It has been suggested that physical exercises prepare the brain for regulatory processes during cognitive training sessions [20]. Although past research has largely supported the effectiveness of combining physical and cognitive exercises [15], two important questions remain unanswered: firstly, considering the wide range of physical and cognitive exercises, which components should be combined. And secondly, how this combination should be done. The previous studies have mostly focused on a single aspect of exercises, with an emphasis on aerobic, coordination, and balance exercises in physical exercises [21–23]. Also, there are researches focused on functions related to working memory, such as shifting and updating and inhibition, in cognitive training [24] Moreover, another challenge that past research has encountered is the type of combination of cognitive and physical exercises. In the combination of cognitive and physical exercises, there are usually different approaches. For example, in one approach, sequential execution of cognitive and physical exercises are considered, i.e., performing physical exercises first and then cognitive exercises, or vice versa [18]. In another approach, i.e. simultaneous execution of physical and cognitive tasks, both types of exercises are presented simultaneously. It has been shown that simultaneous exercises have a greater impact on improving cognitive functions in healthy older adults as well as those with disorders [19]. In the simultaneous approach, two methods have been used. In the first method, which involves dual-tasking, two tasks with physical and cognitive challenges are executed simultaneously without them being related to each other. For example, it has been demonstrated that individuals who participated in a video game with cognitive-motor demands showed greater progress in cognitive and brain functions compared to the physical exercise group alone [25]. Therefore, it appears that the effectiveness of combined cognitive and physical exercise increases when the activities are more realistic and the components are closely aligned.

Based on the above experiences from previous studies, we have used Neurolight that combines cognitive and physical challenges simultaneously and in the form of a single task. Furthermore, Neurolight allows control over the physical and cognitive exercise components by changing the stimulation time and the time between different stimuli. The game-based approach (Exergame) was used in Neurolight, which research shows that this approach can increase the motivation of participation [26]. In the current study, the effectiveness of this type of exercise in improving the cognitive and motor functions of cognitive functions of individuals in the young-old period between the ages of 60 and 69 was investigated. This age group was selected because it is essentially the boundary between adulthood and old age [27]. Therefore, it seems that starting exercises in this period can prevent cognitive decline in later stages of life. For this purpose, individuals were divided into three training groups, one group engaging in cognitive-motor training using the Neurolight system, while another group performed a computer-based cognitive training (Maghzineh), and the last group served as the control. Then, the process of changes in the core executive functions and motor performance of individuals before and after the exercises in different groups was examined to answer the question of how effective these exercises are in improving cognitive and motor functions.

The present research employed a semi-experimental design using pre-test and post-test with a control group. The sample included 36 elderly people aged 60 to 69 who volunteered to participate in this study and were selected based on the inclusion criteria. The inclusion criteria for this research included no mobility restrictions, normal intelligence, and the ability to use an online system. Participants were randomly assigned to three groups: the control group (12 participants) continued their daily activities, while the intervention group (12 participants) underwent a cognitive-motor training program using the Neurolight system for 24 sessions, and the third group (12 participants) performed a computer-based cognitive training package, called Maghzineh, for 24 sessions.

Materials

Neurolight System

This system consists of a hardware and a software components that interacted with each other. The hardware section consists of a series of smart lamps that can be turned on, as stimuli, according to a specified task, and a user's response can be received by touching the lamps. The lamps are placed inside a mat in a triangular form that can be used in different setups, such as on a table, on the floor, or on a wall. Accordingly, this hardware is usable in different protocols such as aerobic and balance-coordination protocols. It should be noted that physical and bodily exercise protocols are divided into three main categories, which have the greatest impact on improving executive functions, including balance, aerobic, and coordination exercises [21–23]. The balance exercises are divided into static and dynamic, in which individuals have to perform cognitive challenges while maintaining balance simultaneously. Such tasks, simulates several activities that the elderly perform during the day. The aim of aerobic exercises is to increase heart rate, which was regulated based on the change in the speed of stimulus presentation rhythm and subsequent execution of movements. Accordingly, similar tasks are developed in the Neurolight system with a specific rhythm and sequence that places individuals in the aerobic exercise situation. The third category of movements involved coordination, aiming for unilateral and bilateral coordination, i.e., between the right and left sides. For example, the individual had to perform movements bilaterally with a specific rhythm, such as 2 movements to the right and 3 movements to the left. The Cognitive challenges were mostly based on the two components of working memory and inhibition which was combined with physical exercises. The hardware is controlled by the software component. The tasks are based on the type of physical and cognitive challenges, as well as the specific exercise intensity. The software component is designed as a mobile application for use on smartphones or tablets. The tasks and responses of users are collected on saved on a server for user performance analysis. This stored data include response speed, number of correct and incorrect responses in each task, and tasks information.

Maghzineh

A cognitive training program called "Maghzineh" has been used in the form of two platforms, a web-based version for training with laptops and an Android version for training with mobile devices. This program consists of 24 cognitive training sessions based on attention and working memory, with the difficulty of the exercises gradually increasing. In this regard, individuals were unaware of the cognitive goals of games and were only focused on earning points and progressing through the levels of the game. The efficacy of this package had been previously confirmed by researchers in the field of cognitive rehabilitation [28]

N-Back Test

The N-Back test has been used to assess working memory [29]. In this test, a series of visual stimuli appears sequentially on the display screen, and an individual has to press the target key if each stimulus resembled the stimuli presented earlier. The visual stimuli consisted of several random numbers displayed separately on the screen, and the individual had to decide whether the presented number matched the two previous numbers presented (2-back). Accordingly, with the presentation of a new stimulus, the sequence of the two preceding numbers continuously changed. In this task, two main operations of working memory, namely, information retention and updating, are executed. New information is analyzed simultaneously and in real-time, compared with previously stored information, and provide guidance for decision-making. Variables such as error rate and number of correct responses were measured as indicators of performance accuracy, while reaction time index served as a measure of information processing speed and the variability of reaction time index in correct attempts served as an indicator of performance consistency or attention maintenance during task, were examined as the output results of this test.

Stroop Test

The Stroop test is a common task in psychology used to assess executive functions, particularly inhibitory control. In this test, participants are required to name the color of words written in different colors, regardless of their meaning [30]. In this study, a software version of task was utilized, consisting of 48 congruent color words and 48 incongruent color words written in red, blue, yellow, and green, presented to the participants. Congruent words refer to words where the color matches the meaning, while incongruent words refer to words where the color differs from the meaning. In total, 96 color words, congruent and incongruent, are randomly and sequentially presented in this test. Inhibitory control or interference score is calculated by subtracting the score of incongruent errors from the score of congruent errors. Additionally, a longer average response time to incongruent stimuli compared to congruent stimuli is considered another indicator of interference, known as the interference time, calculated by the difference in reaction time in incongruent attempts compared to congruent attempts [31].

Timed Up and Go Test (TUG)

The Timed Up and Go (TUG) test is a modified version of the Get Up and Go test used to assess balance. The procedure for this test involves the participant sitting on a standardized chair (with a height of 46 cm and armrest height of 63 cm), then upon hearing the command from the examiner, rising from the chair, walking a distance of 3 meters in their normal pace forward, turning, returning to the chair, and sitting back down. During this process, the examiner records the time using a stopwatch. Scores are interpreted as follows: achieving a time record of less than 10 seconds indicates high and natural mobility, achieving a record of 10 to 19 seconds indicates normal mobility and independence in walking, achieving a record of 20 to 29 seconds indicates slower movement, balance impairment, and need for assistance in walking, and recording a time of over 30 seconds indicates reduced mobility and susceptibility to falls in older adults [32].

Data Collection

Initially, 36 elderly aged between 60 and 69, who visited the Omid Cultural Center of the Tehran Municipality, were selected through registration announcements and having entry criteria readily available. Then, these individuals were randomly assigned into three groups: the physical cognitive exercises group (Neurolight), the computer-based cognitive training group (Maghzineh), and control group. At the beginning of the experiment, their working memory was evaluated using the N-Back test, inhibition was assessed using the Stroop test, and mobility was assessed using the TUG test. Subsequently, individuals in the computerized cognitive training group engaged in attention and working memory training using the Maghzineh program. In the Neurolight group, individuals, in addition to cognitive components, performed balance, coordination, and aerobic exercises, while the control group only participated in daily activities. After completing the sessions, all three groups underwent the aforementioned tests again to examine the trends of changes over this time period. Furthermore, to test the research hypotheses, analysis of covariance was utilized.

For outlier value detection, for both single and multivariate variables, Cook's distance and Mahalanobis distances were used. The results indicated that none of the data had a Cook's distance exceeding 0.6, suggesting that there were no outlier data points present in the dataset [33]. However, the outliers of each group were also examined using Mahalanobis statistics at the α = 0.01 level, yielding similar results [34]. To assess the normality assumption, multivariate statistics based on the de Carlo macro (1997) were employed for the four continuous variables. For brevity, the focus here is on Small's (1980) and Srivistava’s (1984) tests of multivariate kurtosis and skewness, Mardia's (1970) multivariate kurtosis. Also, the test of multivariate normality based on Small's statistic [34] were used. The results are presented in Table 1.

Tables 1. Multivariate normality hypothesis tests

Multivariate skewness test	Statistics	df	p-value
Small's test	VQ1 = 6.99	4.00	0.1359
Srivistava’s test	chi(b1p) = 4.06	4.00	0.3968
multivariate kurtosis	Statistics	df	p-value
Small's test	VQ2 = 5.00	4.00	0.2873
Srivistava’s test	chi(b2p) = 2.25	N(b2p)=-1.82	0.0680
Mardia's test	b2p = 19.07	N(b2p)= -2.13	0.0328

These results indicate that the assumption of multivariate normality for the variables is acceptable. Then, the Box's M test and Levine's test were employed to test the homogeneity assumption of both multivariate and univariate variances. The Box's M statistic was 53.43 and non-significant (F = 1.382, df1 = 30, df2 = 3450.72, p > 0.05), indicating the non-significance of Box's M test. The results of Levine's test also showed non-significance with all p-values greater than α > 0.09, indicating homogeneity of univariate variances.

In Table 2, the descriptive statistics are shown. The results of covariance analysis showed that there is a significant difference between the groups in the interference score variable (F_{2, 32}=3.34, P = 0.048, η² = 0.173). Pairwise comparisons indicated a significant difference observed between the Neurolight and control groups (P = 0.01), On the other hand, no significant difference were observed between the Neurolight and Maghzineh groups as well as between Maghzineh and control groups (P > 0.05). In the time interference component, although the trend of changes in all three groups is decreasing, there is a significant difference between groups in the posttest phase (F_{2, 32} =3.79, P = 0.03, η² = 0.19). The pairwise comparisons between groups showed a significant difference between the Maghzineh and Neurolight groups (P = 0.01), while no significant difference was found between the other groups.

Table 2

Descriptive Statistics
Tests		Stroop		N-Back			TUG
Variables Group		Interference score	Interference Time	Correct Numbers	Reaction Time	Reaction Time SD	Time
Neurolight	Pre-test	3.65	100.75	76.58	638.42	259.00	9.14
Neurolight	Post-test	2.14	68.08	82.42	551.25	207.92	8.17
Maghzineh	Pre-test	4	61.33	99.33	867.08	245.17	8.28
Maghzineh	Post-test	3.83	14.42	106.58	928.5	236.58	8.54
Control	Pre-test	1.68	71.92	89.33	608.92	192.75	8.53
Control	Post-test	3.19	50.42	90.33	571.83	237.58	8.69

The results of the covariance analysis in the correct response (F_{1, 32}=1.78, P = 018, η² = 0.1) and the reaction time (F_1,32=63.7, P = 0.0001, η² = 0.79) of the N-back test showed no significant difference between the groups, and all groups showed a similar trend of improvement from pretest to posttest. Although, the findings in the reaction time variability in the N-back test indicated a significant difference between the groups in the posttest phase (F_1,32=3.64, P = 0.038, η² = 0.19). The pairwise comparisons results showed that the Neurolight group performed significantly better than the Maghzineh (P = 0.044) and control groups (P = 0.017).

According to the information obtained from the covariance analysis in the balance test, it was determined that there was a significant difference between the groups scores in the posttest phase (F_{2, 32}=6.09, P = 0.006, η² = 0.27). The pairwise comparisons revealed significant differences between the Neurolight and Maghzineh groups (P = 0.021), as well as between the Neurolight and control groups (P = 0.002), indicating a greater decrease in movement time in the Neurolight group.

The results related to the Stroop test, aimed at evaluating cognitive inhibition in individuals, in two dimensions of interference score and interference time, showed differences. While in the interference score component, the Neurolight group showed greater improvement, in the interference time component, the cognitive training group performed better. These results can be discussed from two perspectives. First, both cognitive and combined physical-cognitive training have improved individuals' inhibition, but the effectiveness differences of these two types of training can be noted. For a more precise analysis of this phenomenon, attention should be drawn to how these two components are calculated. While the interference score is the result of the difference in the number of errors individuals make in congruent versus incongruent trials, the Neurolight group was able to reduce errors in incongruent trials. In other words, they could better control the interference resulting from color processing versus word meaning processing, indicating improved performance resulting from this type of training. On the other hand, it appears that only when individuals can improve performance accuracy or interference score, the evaluation of interference time becomes meaningful. In this regard, there is a possibility that the improvement in interference time or the increase in speed in incongruent trials may result in decreased performance accuracy and consequently increased interference score. Therefore, since maintaining accuracy alongside speed is the main instruction in these types of tests [30], doubts exist regarding whether the improvement in interference time alone can indicate interference control. Consequently, it can be inferred that the reduction in impulsivity and impatience in controlling responses and the increase in performance accuracy in incongruent trials due to the combination of cognitive and physical training have occurred, which can be considered among the advantages of this type of training. Furthermore, because computer-based cognitive training involve sitting behind a computer or tablet, individuals may become accustomed to rapid responses and somewhat conditioned to it. In this regard, Ten Brinke et al. demonstrated that both cognitive and cognitive-physical training can lead to similar .improvements in Stroop test performance [10].

The results of the n-back memory test indicated that there was no significant difference between the groups in terms of the number of correct responses, and the progress trend from pre-test to post-test was almost the same across groups. However, in terms of the reaction time variability, the cognitive-physical training group showed better performance. Since this component is related to the processing speed, it seems that the rapid updating of information, which is one of the foundational components of executive control in working memory [35], has been enhanced as a result of these exercises. Furthermore, the reduction in the reaction time variability due to Neurolight training may be an indicator of improved central attention and auditory processing ability [36]. Considering the hierarchical model of executive functions that attention is involved in both working memory and inhibition tasks [3], it appears that attentional capabilities have been enhanced as a result of Neurolight exergame. These findings align with studies which have reported beneficial effects of combining the cognitive and physical exercises [26, 37, 38]. Based on the cognitive stimulation hypothesis, physical activities coordinated with cognitive demands activate the same brain regions used for higher-level cognitive control processes [13, 39]. For the relationship between physical activity and cognition, the assumption is that cognitive demands, when pre-activated by the same cognitive processes during physical activity as in a cognitive task, lead to better cognitive performance [40]. In this regard, it has been demonstrated that cognitive-motor Exergames improve neural efficiency, which can manifest in faster information processing [38]. Also, it has been reported improvements in information processing speed as a result of this type of training [26]. However, Adcock et al. showed that although improvements in executive functions were observed in elderly individuals as a result of cognitive-motor exercises, no noticeable changes in brain gray matter were observed [41].

One concept that can be discussed in this regard is the topic of cognitive training. These trainings, such as computer-based training, which target memory, attention, and visual and auditory processing, are associated with cognitive enhancement in healthy older individuals. However, their effectiveness, especially in terms of transfer to real-world situations, is debatable [42]. Other studies using the same intervention method have also shown that engaging in brain training games improves executive function and processing speed in healthy older individuals [43]. However, most studies indicate that the effect size for cognitive interventions alone is very small [42, 44]. Therefore, based on the current findings, it may be possible to enhance their effectiveness by combining cognitive and physical exercises. Evidence suggests that cognitive and physical training may complement each other and contribute to improving brain structure and function and cognition [19, 45].

These findings can be discussed in terms of how the cognitive challenges in the Neurolight protocol can enhance cognitive functions. This finding is supported by research showing that motor coordination and balance exercises can also have positive effects on cognitive functions [46–49]. It has been showed that exercises involving both balance and cognitive challenges reduce activity in the right and left prefrontal cortex during walking, indicating greater efficiency and freeing up attentional resources for other tasks [25]. Also, it has been demonstrated the role of the prefrontal cortex and its lateral posterior component in performing balance tasks [50]. Accordingly, performing balance tasks activates these regions, which play a role in higher brain functions such as inhibition and working memory. Based on this perspective, executive functions are primarily associated with the prefrontal cortex and other related brain regions, and interventions that affect the prefrontal cortex may also affect executive functions [51].

Finally, in addition to analyzing the physical and cognitive benefits of Neurolight exercises, it can be noted that in this type of exercise, individuals spend time equivalent to one exercise session, but benefit simultaneously from the advantages of both physical and cognitive exercises. This means that motor skills, physical fitness, and cognitive functions are practiced simultaneously. Liao et al. showed that the combination of cognitive Exergames not only improves cognitive function but also affects individuals' walking performance, although this effect was observed only in dual-task walking [38]. There is evidence that confirmed the effectiveness of cognitive Exergames in improving motor cognitive functions, which play a role in preventing falls in the elderly [52]. Also, it has been demonstrated that cognitive-motor game-based exercises not only improve cognitive function but also enhance motor performance [53]. This finding is consistent with the observed improvement in motor performance in the elderly in this study, indicating a common basis for motor and cognitive aspects in this age group. Therefore, it seems that adding motor challenges such as balance and fine movements to aerobic exercises has increased the cognitive demand of the exercise, resulting in observed beneficial effects [54]. On the other hand, it is also possible that aerobic exercises act as a trigger to prepare individuals for subsequent exercise interventions, in addition to any positive physiological effects it may have [55]. In this regard, the effects of aerobic exercise appear to have synergized with the motor skill exercises used in the present study, enhancing their effectiveness. It is suggested that a combined cognitive and physical intervention may have greater benefits for cognition compared to either intervention alone. In the aspect of combining cognitive exercises with physical challenges, two points can be noted: firstly, cognitive and physical exercises are paired and enhanced each other's relative effects, and more cognitive activities occur during movement in individuals' daily lives. On the other hand, fewer cognitive decisions and activities performed in isolated environments. In this regard, there is finding that combining cognitive and motor exercises in adults can prevent cognitive decline in adulthood and thus prevent aging [56].

The present results can be considered as a preliminary study in the effectiveness of cognitive-physical exercises using the Neurolight system. Based on its findings, the use of this exercise system can be suggested to coaches and therapists working with the elderly. However, the extends of its use and effectiveness range can be further tested in future research. Therefore, future research could focus on increasing the utilization of the system, improving software, hardware, and user interface. Additionally, by examining and analyzing internal data within the exercise period, the trend of changes and increasing the level of intelligent difficulty can be more fully demonstrated. Moreover, this system can be evaluated for cognitive disorders such as learning disabilities, Attention Deficit and Hyperactivity Disorder (ADHD), and other age groups.

Ethics approval and consent to participate

All procedures were in accordance with the ethical standards University of Tehran research committee and approved by the Research Ethics Committee (code: IR.UT.PSYEDU.REC.1402.043). After giving the initial instruction about the study, informed written consent was obtained from all participants. All of them participated in this study voluntarily.

Consent for publication

We provide consent for the publication of the manuscript

Funding

This project has been supported by the “Iranian Cognitive Sciences and Technologies Council Vise-Presidency for Science and Technology”

Authors' contributions

MG and HM contributed to the development of the protocol and preparation of the manuscript as well as reviewing and editing. MT and PM contributed to the data collection and EZ contributed to the data analysis.

Author details

Faculty of physical education and sport sciences, Allameh Tabataba'i University, Tehran, Iran
Professor, Chair of Robotics and Machine Intelligence Group, School of Electrical and Computer Engineering, University of Tehran, Iran.
Assistant professor of assessment and measurement, Faculty of psychology and education, Allameh Tabataba'i University, Tehran, Iran

Conflict of interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Acknowledgments

The authors are grateful to all participants, and trainers who cooperated in this study.

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No competing interests reported.

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Computerized Cognitive games versus Cognitive Exergame: The comparison of motor and cognitive functions enhancement in late-adulthood

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Abstract

Background

Methods

Results

Conclusion

Introduction

Methods

Materials

Neurolight System

Maghzineh

N-Back Test

Stroop Test

Timed Up and Go Test (TUG)

Data Collection

Results

Discussion

Declarations

References

Additional Declarations

Status:

Version 1