1 Introduction

The knees bear most of the weight of a human body. Therefore, excessive weight loading causes knee degeneration and makes knees more susceptible to disease. Osteoarthritis (OA) causes joint stiffness, pain and deformation. Patients find difficulty in walking and performing routine daily tasks. Severe disease and pain require patients to undergo joint replacement surgery, in order to improve their joint functioning and self-care ability. The number of people accepting total knee replacement (TKR) has been increasing, year by year. In Taiwan, about ten thousand people have a TKR every year. Once a patient decides to have a TKR, the uncomfortable, tedious and long-term postoperative rehabilitation process is a challenge they need to face. Rehabilitants often show a lessened endurance in participating in the rehabilitation process, which results in further muscle atrophy.

Therapists are concerned with how to make patients rehabilitate effectively over the course of years. In recent years, there have been many studies using virtual reality technologies and motion-based games as intervention tools in rehabilitation. Virtual reality (VR) is defined as “the use of interactive simulations created with computer hardware and software to present users with opportunities to engage in environments that appear to be and feel similar to real world objects and events” [26]. VR provides rehabilitants with a safe access to interactive and realistic situations that would otherwise be inaccessible to them, due to their motor limitations [17, 21]. It’s relatively easy to change a virtual environment, adapting it according to the user’s capabilities [18]. People enjoy using virtual environments [19]. Moreover, the use of a VR can increase motivation for treatment and rehabilitation [10]. Though VR is helpful in rehabilitation, it still has limits. Further, because the high development costs of a VR system, aimed at specific rehabilitant diseases, are passed on to the consumer, not all people with motor disabilities can afford this form of treatment. Additionally, not all the settings are practical for people needing a VR system.

Thus, commercial, motion capture tools, which have a relatively lower development cost, began to be used in this field. Nintendo Wii Remote and Wii Fit have given evidence of being useful physical rehabilitation tools [13]. Motion-based games that combine motion sensor technology and video games can motivate people to engage in exercises [1]. There are, however, still drawbacks with these motion sensors: Wii needs the user to hold the remote; the rehabilitation motions are limited to the upper extremity; and Wii Fit constrains rehabilitants’ movement in the area of the force plate, without which the sensors could not accurately collect data.

Using a Microsoft Kinect™ platform is the best solution. Kinect is a motion-sensing input device, produced by Microsoft for the Xbox 360 video game console and Windows PCs. Based around a webcam-style add-on peripheral for the Xbox 360 console, it allows the user to control it with a game console, and enables the user to interact through a natural user interface, using gestures and without needing to touch a game controller. The Kinect sensor comes with an RGB camera and a depth sensor, which, in combination, provide full-body, 3D motion capture (see Fig. 1). Using Kinect means that the users don’t have to equip any auxiliaries.

Fig 1
figure 1

Kinect sensor

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This study developed a Kinect-based rehabilitation system called Physical Rehabilitation System (PRS), which assists the rehabilitating TKR patient in ways which were rarely noticed by previous studies. A PRS uses the image processing technology of Kinect to detect a rehabilitant’s movements while riding a stationary bicycle, and uses the data to drive an avatar, which races the virtual bicycle in the game. The proposed system solves the problems described above. The Kinect sensor is easy to acquire, and its cost is minimal. Microsoft also provides a Kinect software development kit (SDK), which allows researchers to develop different features aimed at a specific purpose. Using the image processing technology of a Kinect sensor means that participants have more space for activities. Users don’t have to be bothered with body sensors and can be more attentive to their rehabilitation.

The purpose of this study is to try to improve the rehabilitation performance of TKR patients by using the gaming elements of a PRS to motivate those who have to endure a tedious rehabilitation exercise regimen. Accordingly, this system has the following features: (a) a bike-racing gaming element with audio and video feedback, used to reinforce rehabilitants’ motivation; and (b) a data recording to note rehabilitants’ behavior with regard to speed, time and score.

2 Related work

2.1 Game-based rehabilitation

One study indicated that only 31 % of rehabilitants performed the daily exercises recommended by their therapists [22]. Many solutions have been proposed to improve the rehabilitation performance by strengthening rehabilitant motivation. Game-based rehabilitation was reported as early as 30 years ago, but had been ignored for a long time [27]. In recent years, a great deal of research has proven that the game-based approach can really strengthen rehabilitants’ motivation and improve performance, as well. Jack [10] used a PC-based, desktop virtual reality system for rehabilitating the hand function of stroke patients. Video games were used by O’Connor [15] in an attempt to increase the physiological responses of people with spinal cord injuries (SCI), and to examine the games’ effect on their motivation. The results showed that 87 % of the participants found that the games motivated them to perform their exercises. Betker [2] also demonstrated that the interactive gaming environment could motivate participants to practice dynamic movement tasks.

With the popularity of motion capture technologies, commercial motion sensors, such as Nintendo Wii, Wii Fit and Microsoft Kinect, have been applied to the rehabilitation field. Researchers have increasingly investigated the feasibility and effectiveness of lower-cost, commercially available technologies, such as virtual reality video gaming systems, as potential rehabilitation interventions [6, 9]. Further, many studies show that VR-based intervention and commercially available motion capture tools are both feasible and suitable for rehabilitation [5, 14].

2.2 ARCS model

It has been demonstrated that motivation can affect rehabilitation outcomes [9.2]. Keller [11] proposed the ARCS model, a problem solving approach towards designing the motivational aspects of learning environments to stimulate and sustain students’ motivation to learn. The ARCS model identifies four essential strategies for motivation instruction:

  • Attention: to arouse interest and stimulate curiosity.

  • Relevance: to link student needs, interests and motives.

  • Confidence: to help develop a positive expectation for successful achievement.

  • Satisfaction: to provide extrinsic and intrinsic reinforcement for effort.

The ARCS model is divided into four categories (see Table 1), each of which offers assistance in one of the above mentioned areas.

Table 1 ARCS categories
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There was no precedent for a study using the ARCS model in a rehabilitation context before our study. However, the processes of the ARCS model in the learning field are similar to those in rehabilitation: they arouse participants’ attention and curiosity for something, and find the relationship with it; they let participants believe “[they] have the ability and confidence to deal with it”; and, upon completion, they have the satisfaction of accomplishment. Therefore, it is possible that the ARCS model would suit the rehabilitation context.

2.3 System usability scale

Usability is not a quality that exists in any real or absolute sense [3]; it has different definitions in different contexts. For example, if different people used the same system in different environments to achieve different purposes, the cognition would be different. In other words, there are no absolute measures of system usability.

The system usability scale (SUS) was developed by John Brooke in 1986. A SUS is a subjective perception scale, often used to test product usability. This helps product developers understand the usability of their product, and how it may compete with other, similar products. A SUS is a ten-item Likert scale, giving a global view of a subjective assessment of usability. At the same time, data collection and analysis can meet the needs of enterprises relatively simply.

SUS requires responses to ten statements, as follows:

  • I think that I would like to use this system frequently.

  • I found the system unnecessarily complex.

  • I thought the system was easy to use.

  • I think that I would need the support of a technical person to be able to use this system.

  • I found the various functions in this system were well integrated.

  • I thought there was too much inconsistency in this system.

  • I would imagine that most people would learn to use this system very quickly.

  • I found the system very cumbersome to use.

  • I felt very confident using the system.

  • I needed to learn a lot of things before I could start using this system.

Each statement requires a response on a 1–5 scale, 1 indicating the user completely disagrees with the statement, to 5, indicating the user strongly agrees with it. The scoring rules of the system usability scale are described, as follows: divide the ten statements into two groups, odd-number (positive) questions and even-number (negative) statements, each statement carries a zero-weight score between 1 and 5. Each original score of a positive statement receives −1, while −5 is received for each no weighted score of a negative statement. The total of these ten scores, multiplied by 2.5, is the SUS score, which is a single score, based on a scale of 1–100.

2.4 Self-determination theory

Self-Determination Theory (SDT) [7] represents a broad framework for the study of human motivation and personality. SDT proposes that people are organisms with innate psychological growth and developmental potential. Self-determination is the making of a choice, based on the belief that the individual can exert an influence on the outcome of important life events, and which guides people to engage in interesting and beneficial behavior; it is based on full understanding of individual needs and environmental information. SDT identifies three innate psychological needs that, if satisfied, allow optimal function and growth:

  • Competence: the psychological need to resolve issues effectively and efficiently

  • Relatedness: the psychological need to establish close relationships with others.

  • Autonomy: the psychological need to be self-directed and affirm that behavior is spontaneous.

According to SDT, motivation is divided into three types:

  • Intrinsic motivation: a high degree of autonomous motivation, coming from the psychological needs of interest and pleasure.

  • Extrinsic motivation: motivated, not because of interest in a particular activity, but in order to obtain some separate result, such as gaining a high score or avoiding punishment.

  • Amotivation: a low degree of autonomous motivation, and no interest in engaging in activities.

SDT has been widely applied in learning and sports injury contexts. Autonomous forms of motivation have been shown to have positive predictability, while controlled forms of motivation had a negative or non-significant predictability [4].

3 Method

This section introduces the research concept, which investigated the relationship between PRS usage and rehabilitation achievements, based on ARCS theory. This study researched the effect of game-play in a rehabilitation situation, by combining the physical rehabilitation strategies and elements of motion capture games. The goal was to determine whether commercial motion capture tools could support the traditional rehabilitation approach by observing rehabilitants motivational changes and influencing the rehabilitation achievement.

In the past, there were some studies, using Nintendo Wii and Wii Fit, which demonstrated significant success in helping patients recover from sports injuries. They proved the feasibility of using commercial motion-sensing tools in rehabilitation. Also, these kinds of commercial tools had the additional advantages of being easy to acquire at a low cost and having fewer space restrictions. Unfortunately, Wii and Wii Fit required the user to hold a remote or stand on a balance plate, limiting the parts of the body that could be rehabilited. Also, some users indicated that they felt some discomfort in using these devices for a long period.

To solve the problem of the lack of an appropriate, commercial, motion capture tool for TKR rehabilitants, our team developed a bike-racing game, using a Microsoft Kinect sensor, to help patients recovering from TKR. A PRS does not need the user to hold a remote or wear any other devices. None of the traditional rehabilitation strategies and processes was modified; we only added this Kinect-based game with a stationary bicycle to the active range of motion (ROM). This study addressed the following research questions:

  • Is there a relationship between the rehabilitant’s motivation and the rehabilitation achievement?

  • Is there a relationship between the usability of the system and the rehabilitation achievement?

  • What kinds of demographic variables would likely influence rehabilitation motivation and the perceptions of a PRS?

Figure 2 illustrates a hypothetical model of our study. The variables and hypotheses are described, as follows, according to the literature and our research purpose:

Fig. 2
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Hypothetical model

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3.1 Dependent variable: rehabilitation performance

The rehabilitation performance included measured bending of the rehabilitant’s knee, and whether the participant achieved the rehabilitation criteria. These were normally evaluated by the physical therapist in order to monitor the influences of the PRS.

3.2 Demographic variables

Some studies show there are gender differences in information technology use and implementation [16, 24]. Age is also related to the achievement of computer-based tasks. In general, older adults learned more slowly and made more errors in training tasking [12]. Therefore, we consider that both of these variables are related to system usability. If participants had experience on using similar gaming systems, it meant they were more familiar with this system than those who didn’t have any user experience. This difference may cause different perceptions of system usability. The physical therapists also suggested that a rehabilitant’s exercise habits and related disease affected his/her willingness to participate in rehabilitation activities.

H1 a :

A rehabilitant’s exercise habits will affect rehabilitation motivation.

H1 b :

A rehabilitant’s knee-related disease(s) will affect rehabilitation motivation.

H2 a :

A rehabilitant’s gender will affect perceptions of system usability.

H2 b :

A rehabilitant’s age will affect perceptions of system usability.

H2 c :

A rehabilitant’s experience in using motion capture tools will affect perceptions of system usability.

3.3 Motivation

Many studies had proved that gaming systems can effectively strengthen a rehabilitant’s motivation enough to improve the rehabilitation performance [14, 20]. Physical therapists also suggested that rehabilitants with a higher degree of motivation might have a stronger desire to use an assistance tool or system. In this section, we used the ARCS model to investigate this possibility. The ARCS model was developed to stimulate learning motivation. However, the process of motivation improvement is similar to that of changing rehabilitation motivation. Therefore, we simply try to modify the ARCS questions to make this model applicable in a rehabilitation context. We also suggest that different degrees of motivation may influence the intention of the user, and that perceptions of system usability may cause differing degrees of motivation.

H3 :

Motivation and system usability are related.

H4 :

Motivation will affect the rehabilitation performance.

3.4 System usability

Usability is not a quality that exists in any real or absolute sense [3]. International Organization for Standardization defines usability as “A set of attributes that bear on the effort needed for use, and on the individual assessment of such use, by a stated or implied set of users, and that a better or worse system of usability depends on the subjective consciousness of the user.” It’s easy to understand that a user’s preferences would affect the working performance. In this study, we used a SUS to evaluate the usability of a PRS.

H5 :

Different perceptions of system usability will result in different rehabilitation performances.

A small-sample experiment is designed for this study that nonparametric statistics is applied to the analysis. Nonparametric statistics contains the advantages of being able to apply to variables in nominal or ordinal scale measurements and small-sample tests not corresponding to normal distribution [23, 25]. Nonparametric test therefore could test the variance between two groups with Mann–Whitney U test. Such a method is similar to Independent-Sample T-Test. When the samples are over 20, Vargha and Delaney (2000) [8] proposed the effect size to help nonparametric Mann–Whitney U test as the reference of the significance.

3.5 Participants

This study used a quasi-experiment design. A PRS was designed explicitly for rehabilitants who were recovering from a total knee replacement; these patients could leave their beds and do active ROM exercises, 2 days after surgery. We cooperated with a regional hospital in Kaohsiung, and chose 27 rehabilitants who could ride the stationary bicycle without any assistance. These 27 participants were divided into two groups: one group of 16 served as the experimental group; the other 11 served as the control group. All rehabilitants were treated by the same physical therapist. The participants in the experimental group rode the stationary bicycle with a PRS. The rehabilitants in the control group used the traditional rehabilitation approach, without any aid devices.

3.6 Questionnaire design

To understand the rehabilitants’ perceptions of PRS usability, we designed a series of questions that could be answered, intuitively. First, in order to examine whether the participants’ experience and state of health would influence their motivation and perceptions of a PRS, we collected the necessary demographic variables, to include: gender, age, experience of using motion capture tools, exercise habits, and related diseases (see Table 2).

Table 2 Demographic variables
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In order to allow for easy answering, we simplified the SUS, reducing it to five items, however, we increased the scoring weight from 2.5–5, maintaining the original 0–100 score basis. We also replaced some statement words, enabling them to express the objective more clearly. Table 3 shows the simple SUS. The first, third and fourth questions are negative questions.

Table 3 Simple SUS sample
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To understand the rehabilitant’s motivation, we designed a questionnaire based on the ARCS model (see Table 4).

Table 4 ARCS questionnaire item
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Finally, to identify the different correlations between intrinsic motivation, extrinsic motivation and rehabilitation achievement, we used two simple statements, as in Table 5.

Table 5 Autonomous motivation and controlled motivation
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This questionnaire contains a total 16 statements, listed in Tables 3, 4 and 5. Responses to all questions were on a one- to five-point Likert scale, with 5 representing “strongly agree” down to 1 for “strongly disagree.”

3.7 System development

In this project, we developed a bike-racing game, enabling TKR rehabilitants to have an efficiency active ROM exercise. This system needed to have the ability to distract rehabilitants from their pain in the rehabilitation stage of an active ROM exercise. A PRS was developed on a Unity 3D game engine, and used a Microsoft Kinect™ to catch the motion of rehabilitants so as to drive the avatar, which rides the virtual bike in the bike-racing game.

The gaming interface in Fig. 3 shows that when participants play this game, they have to ride a physical stationary bicycle. The Kinect sensor captures their motions and reflects them in the game. Some barriers and support items appear randomly on the road. If the virtual bike collides with a barrier, the user’s game score is decreased, but by accessing bonus rewards the user may gain points. Rehabilitants have to sway their bodies in order to control the avatar’s making turns, avoiding barriers and accessing bonus rewards. At the same time, there is a notebook, recording all the game content data, including the gaming time and scores.

Fig. 3
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PRS interface: a game menu, b game interface

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3.8 Experiment procedure

This study cooperated with a regional hospital in Kaohsiung, Taiwan, and took 4 weeks to conduct the rehabilitation strategy. It focused on the active ROM exercise stage of the traditional rehabilitation approach, during which rehabilitants rode a stationary bicycle to train their knee joints. The pretest-posttest nonequivalent-groups design in experiment is selected in this study. Total of 27 TKR rehabilitants are proceeded the experiment, the experimental group applies rehabilitation activities and PRS using, while the control group utilizes rehabilitation activities. Both groups use the same procedure with the same activities and contents. Both groups are proceeded rehabilitation activities Pre-test (X1, X3) and CPM (Continuous passive motion) results Post-test (X2, X4). Figure 4 shows our experiment process and the time of each section.

Fig. 4
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Experiment procedure: the physical therapist’s assessment of the daily, rehabilitating results

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3.9 PRS setting

In front of the stationary bicycle, a screen was set up so that rehabilitants could see clearly the gaming scene along with the gaming tips. The Kinect sensor was also set in front of the bike in order to capture the rehabilitant’s every movement. Participants didn’t need to wear any rehabilitation assistance device.

3.10 Intervention phase

The experiment proceeded for a total of six days. Table 6, on the following page, shows the rehabilitation schedule and criteria. All the rehabilitants shared the same rehabilitation process and nursing activities. After daily rehabilitation activities, the participants of the experimental group had to finish the bike-racing game on the PRS, as an additional training exercise.

Table 6 The rehabilitation phase of progressive function
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During the gaming period, the participants of the experimental group rode the stationary bicycle without wearing any aid devices. The Kinect sensor captured the rehabilitant’s motion, relayed it to the avatar, which mirrored the rehabilitant’s activity on the game’s virtual bike. The speed of the virtual bike in the game depended on the rapidity with which the rehabilitants pedaled. In this game, there were some items on the road. Rehabilitants needed to sway their bodies to cause their avatar to make turns in order to get the support items or to avoid the barriers. At the end, as feedback, this game gave scores, reflective of the gaming performance of the participant. Finally, the therapist tested whether rehabilitants achieved the angle criteria of knee flexion.

This section was performed once a day. When participants rode the stationary bicycle, the physical therapist offered the necessary guidance and monitored the rehabilitants’ recovery, making sure that no accidents occurred during this period.

4 Results

With Nonparametric test therefore could test the variance between two groups with Mann–Whitney U-test, the mean pretest of the experimental group is 41 and 40 knee-bending angles of the control group. There is no difference (P > 0.5) in the pretest between the experimental group and the control group, but remarkable differences (P < 0.001) in the posttest. Above two groups are divided in this experiment that “K independent samples” statistics in SPSS is utilized, called Kruskal-Wallis (K-W) test in short. The variance appears when the significance reaches .05, and then Mann–Whitney is proceeded the post hoc. In the Mann–Whitney U test, it is found that a large effect shows when U Test = 1.0, P < 0.025, effect size A = 0.96 [25]. Having applied the rehabilitation activities and PRS using, the control group does not reveal obvious differences on the posttest.

In this study, TKR rehabilitants’ motivation was measured and the effect of different strategies on rehabilitation achievement was analyzed. There were a total of 27 TKR rehabilitants participating in this study, of which 16 were in the experimental group, and 11 in the control group. The distribution was based on the participants’ choice. The full model of hypothesized relationships was statistically tested, using SPSS; the significance level was set at p ≤ 0.05 for statistical analysis. Descriptive statistics, including frequencies, means and standard deviations, were used to calculate subject responses to the statements on the questionnaire. The motivation of the statistical results of the questionnaire, system usability, rehabilitants’ achievement and the differences between the experimental group and the control group were obtained using an nonparametric Mann–Whitney U test and regression analysis. To investigate the relations between rehabilitants’ motivation and system usability, a correlate analysis was used.

4.1 Data analysis of questionnaire

The questionnaire shown in section 3 was designed with the rehabilitants of the experimental group in mind. There were 16 participants rehabilitating with the PRS, consisting of 6 males (mean age = 65.50, SD = 3.391) and 10 females (mean age = 65.80, SD = 4.98). Among these 16 rehabilitants, 7 (44 %) had experience in using motion capture tools, 9 (56 %) had regular exercise habits, and 7 (44 %) had previous knee-related diseases.

The detailed statistical results of the four dimensions of the ARCS questions are shown in Fig. 5. The total average of the questionnaire was 4.14 points, which shows the rehabilitation motivation of rehabilitants was positive. We classified the rehabilitants’ motivation as either autonomous or controlled. For example, if the participant had a higher score on the spontaneous motivation item than on the passive one, s/he would be considered as a rehabilitant with autonomous motivation. In system usability, the participants of the experimental group scored an average of 80.94 (SD = 14.74), which shows that the PRS was acceptable. In the gaming achievement, the experimental participants scored an average of 90.31 (SD = 8.46), with an average gaming time of 174.75 s (SD = 35.03).

Fig 5
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Average score of the ARCS questions

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4.2 Results of hypothesis test

To test hypotheses 1 and 2, an independent sample nonparametric Mann–Whitney U test was performed to test for statistically significant disparities in motivation and in perceptions of PRS usability between rehabilitants with different demographic variables. The motivation and the SUS scores were used as dependent variables, and the demographic variable was used as the independent variable in the test. Also, linear regression was used to examine which demographic variable might affect the motivation and the perceptions of PRS usability.

As shown in Table 7, male and female rehabilitants paid significantly different attention to their rehabilitation activities (p = .049). Responses to item R (Relevance) indicated that there was a meaningful variance in rehabilitation motivation between rehabilitants with daily exercise habits and those without (p = .046). The same responses of relevance were found between rehabilitants with knee-related diseases and those who were healthy (p = .046). Also, responses to SUS (System usability) indicated that there was a significant difference in perception of PRS usability among different age groups (p = .004), experience in using motion capture tools (p = .003), exercise habit (p = .007), and knee-related disease (p = .007).

Table 7 Differences in demographic variables of rehabilitants’ motivation and perceptions of PRS usability
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To find the factors affecting rehabilitants’ motivation and perceptions of PRS usability, linear regression was used. Results shown in Table 8 indicate that gender affected attention (p = .049), exercise habit affected relevance (p = .046), and user experience affected the system usability (p = .003).

Table 8 The analysis of demographic variables on dimensions A, R of ARCS, and system usability
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For testing hypothesis 3, a correlation coefficient was performed to test the association between rehabilitation motivation and perceptions of PRS usability. Table 9 shows the correlation between rehabilitation motivation and perceptions of PRS usability. Item M represents the motivation types, which include autonomous and controlled motivation. There were significant and positive correlations between autonomous motivation and the four dimensions of ARCS (p < .001). Further, the perception of PRS usability was also a significant and positive correlative with item R (p < .001).

Table 9 Correlations among motivation types, ARCS, and perceptions of PRS usability
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An independent sample nonparametric Mann–Whitney U-Test was performed to test for statistically significant disparities in rehabilitation performances, measured as knee-bending angles, gaming score, and gaming time between rehabilitants with different motivation and perceptions of PRS usability. The results shown in Table 10 indicate that there were significant differences in gaming scores, gaming times and knee-bending angles among the rehabilitants with different levels of motivation. The rehabilitants who achieved better performances generally had higher degrees of attention, relevance and confidence.

Table 10 The difference in rehabilitation performances, based on rehabilitants’ motivation and perceptions of PRS usability
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For testing hypothesis 4, a linear regression was used to ascertain which factors affected rehabilitation performances. Results shown in Table 11 indicate that satisfaction affected the rehabilitation and gaming achievement. Further, the results shown in Table 12 demonstrate that PRS usability also caused different rehabilitation performances on knee-bending angles, which supports hypothesis 5.

Table 11 The analysis of motivations on rehabilitation and gaming performances
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Table 12 The analysis of PRS usability on rehabilitation and gaming performances
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Finally, to prove that the PRS intervention was effective, an independent sample nonparametric Mann–Whitney U test was performed to distinguish among rehabilitants with different rehabilitation conditions, statistically significant disparities in their rehabilitation achievements with regard to knee-bending angles. For this part, because of the limited number of rehabilitants, the significance level was set at p ≤ 0.1. The results shown in Table 13 indicate there were significant differences in the rehabilitation achievements among rehabilitants with different rehabilitation conditions. Fig. 6 shows the rehabilitants’ average daily rate of improvement. On the first day of the rehabilitation program, the experimental and control group performed similarly with regard to their average knee-bending angle (40.94 and 40.91, respectively). However, the experimental group, subsequently, showed greater improvement. On the 6th day, the rehabilitants in the experimental group showed an average bending angle of 109.38.

Table 13 The effect of different rehabilitation conditions on the rehabilitation achievement (knee-bending angles)
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Fig 6
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The progression of rehabilitants’ average daily improvement

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5 Conclusion

This study aimed at investigating how different types of rehabilitation motivation affect rehabilitation achievement, and tried to reinforce rehabilitants’ motivation by using a 3D game-based approach to enhance rehabilitation achievement. Participants were divided into experimental and control groups. The participants of the experimental group used a PRS to assist in their daily rehabilitation, and filled out a questionnaire, which was used as the basis for exploring the association among variables; the control group performed general rehabilitation processes and collected rehabilitation results in order to find out whether using a PRS had significantly affected rehabilitation assistance.

Considering the given parameters, the findings of this study were, as follows:

5.1 Demographic variables

The demographic, variable-related findings were integrated, as follows:

  1. (a)

    There were significant differences in attention between male and female rehabilitants; men were more able to focus on rehabilitation activities than women were.

  2. (b)

    Younger participants (age ≤ 65) could adapt to using the PRS more quickly than older participants, and their acceptability of the PRS was higher than that of the older participants

  3. (c)

    Predictably, participants who had experience in using motion capture tools were more facile with the bike-racing game of the PRS, because they were familiar with similar devices.

  4. (d)

    Participants with regular exercise habits responded better to the PRS, since the bike-racing game provided relevance to their daily life experience. Also, rehabilitants with the habit of exercising regularly were in better physical coordination, which permitted them to operate the motion capture tools at a faster pace.

  5. (e)

    Unexpectedly, there were significant differences in dimension R (Relevance) and in the perception of PRS usability between rehabilitants with and without knee-related diseases. The rehabilitants without knee-related diseases had a greater relevance and perception of PRS usability than the rehabilitants in the other group. The reason might be based on an additional discovery related to finding (d), and described in (f).

  6. (f)

    In our questionnaire samples, the rehabilitants who exercised regularly were without a related disease; conversely, all of the rehabilitants who did not exercise regularly had knee-related diseases. From this we infer that the people who exercised regularly had better overall health.

5.2 Motivation and PRS usability

Rehabilitants’ autonomous motivation positively correlated with the four dimensions of ARCS. In other words, the participants driven by intrinsic motivation spontaneously carried out rehabilitation activities, making each ARCS dimension more potent. The usability of a PRS positively correlated with dimension R (Relevance) of ARCS because it provided rehabilitants with the virtual reality of bike-riding. Our experimental result was similar to those of previous studies, showing that rehabilitants with stronger motivation performed better in gaming time, gaming scores and knee-bending angles. The system usability of a PRS also proved helpful in reinforcing motivation and rehabilitation achievements.

5.3 Effects of intervention

To further demonstrate that a PRS was helpful to rehabilitation achievements, we set up a control group to compare rehabilitation outcomes with the experimental group. The results also indicated that a PRS could, in fact, help rehabilitants achieve their rehabilitation criteria more easily. Based on the above discussion, we might even use the participants’ perceptions of system usability, motivation and part of the gaming contents to predict the effectiveness of the rehabilitation.

Accordingly, Table 14 shows the results and indicates whether the experimental outcomes support our hypotheses, as enumerated in section 3.

Table 14 Hypothesis is supported or not
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5.4 Conclusion and future works

This study has proposed a solution to enhance the TKR rehabilitation performance of patients by strengthening their motivation in a 3D game-based rehabilitation environment. This study designed a physical rehabilitation system, which contained a bike-racing game, operated by a Kinect sensor, to help rehabilitants improve their performance. The results showed that motivation affected the quality and pace of rehabilitation, and that this auxiliary system’s acceptance by rehabilitants enabled them to strengthen their motivation and improve their outcomes. These findings can be useful references for future researchers, who aspire to design auxiliary tools and to help physical therapists to improve rehabilitants’ performances.

In the future, we hope to ameliorate the problem of insufficient samples by collecting more data, which would make our results more precise. Although, the rehabilitation systems for different diseases have been developed, but some of the devices still pose restrictions, which must be addressed. For example, a Kinect sensor cannot currently capture finger movements. However, more diverse games from which rehabilitants could choose, could be designed, and these could be helpful in attracting more rehabilitant attention.