Rehabilitation refers to a group of treatments intended to improve functionality and lessen disability in people with medical issues as they interact with their surroundings. Certain medical issues may cause impairments to a person’s physical, emotional, or cognitive functioning Cieza (2019). Over the last 30 years, individuals in need of rehabilitation have increased by 63% globally, and the most common cause is due to musculoskeletal disorders Cieza et al. (2020). Therefore, this research will focus on the augmentation of conventional physical rehabilitation.

In recent years there has been a growing trend of “telehealth” and home-based rehabilitation services Shaver (2022); Velez et al. (2023). This shift may be exacerbated by the fact that limited time and resources make it difficult to effectively treat every patient in a hospital setting Fiscella and Epstein (2008). In Japan, the period of rehabilitation covered by insurance is limited Ministry of Health and Welfare (2024). Therefore, there are many chronic patients who cannot undergo rehabilitation after the acute stage. Studies have shown that home-based rehabilitation programs can be an effective option for certain medical conditions and are also perceived as being a more positive and convenient experience than hospital-based rehabilitation Arsenault-Lapierre et al. (2021); Doig et al. (2011). Although effective, patients who took part in a hospital-based rehabilitation program were shown to have better improvements to their mobility, pain, and depression than patients who only received home-based treatments Chen et al. (2023).

The effectiveness of the rehabilitation is largely based on the patient’s adherence to the prescribed treatment Hayden et al. (2005). Adherence is defined as the degree to which a patient’s behavior corresponds with the recommendations from a healthcare provider WHO (2003). Some home-based treatments may include visits from a doctor, but program adherence is harder to regulate than in a hospital setting. There are several factors that may contribute to a patient’s non-adherence.

One of the largest inhibitors to adherence is a patient’s perceived barriers. This is a patient’s own estimation of the level of challenge to a specific behavior or goal Glasgow (2020). This self-estimation may or may not accurately align with the objective challenge of the task. One study showed that patients who were prescribed two daily exercises had significantly higher levels of adherence than patients who were prescribed eight exercises Henry et al. (1999). Similarly, in a study regarding athletes’ adherence to a rehabilitation program after an injury, it was shown that the participants often forgot or claimed to not have time for the exercises Marshall et al. (2012). A part of physical rehabilitation is repeating the same exercises over an extended period of time in an effort to improve certain metrics such as range of motion or strength. These repetitive exercises are often described by the patients as being tedious and uninteresting Burke et al. (2009). This lack of motivation can inhibit rehabilitation efforts and result in delayed or impaired recovery. Home-based rehabilitation can be equally effective, but it necessitates strong patient motivation and regular follow-up appointments Frih et al. (2009).

Depending on the medical condition and severity of the injury, rehabilitation can be a slow and painful process. For example, patients who suffer from spinal cord injuries or strokes receive the highest annual hours of treatment Saumur et al. (2022). Additionally, some medical conditions may require months or years of rehabilitation to achieve full recovery Greenberg et al. (2018). This slow progress can make day-to-day results and feedback difficult to visualize. Lack of positive feedback is a key factor in a patient’s non-adherence to their physical therapy Sluijs et al. (1993).

Loneliness, especially with older adults, is a common issue with home-based rehabilitation Lykke and Handberg (2019). Further, after serious medical complications such as a stroke, patients have also been reported to suffer from depression as well Kotila et al. (1998). These negative feelings of isolation and depression can become an issue for the success of the rehabilitation since emotional support from friends and family is correlated to an increased adherence to a treatment program Levy et al. (2008).

Gamification refers to the process of adding game-like elements to a non-game-related activity Von Bargen et al. (2014). This is typically done for such reasons as increasing motivation or engagement. Studies have since been conducted to better understand how these gamification techniques can be utilized in a therapy setting. Janssen et al. described the similarities between game design and therapy design Janssen et al. (2017). They state that by using game principles, a medical specialist could better tailor a rehabilitation program to meet the needs of an individual. In practice, most gamification research targets the hand, knee, posture, and gait while being augmented by external devices such as robotic exoskeletons or virtual reality Tuah et al. (2021).

In this work, we propose a gamification interface, named Max Well-Being (MWB), that allows for different forms of input to be mapped to any in-game button command. This then creates the flexibility for a medical specialist to adjust a game to fit the medical condition and goals of the patient. The MWB system aims to demonstrate a wider potential for commercial games to be used in traditional rehabilitation methodologies. The future aim of this research is to use the MWB to improve three problems with rehabilitation; motivation, feedback, and isolation. However, the current goals of this study are to i) propose a method of selecting a commercial video game for physical rehabilitation, ii) verify the performance of the hardware and software components, and iii) determine the overall usability of the system by both medical specialists and potential end users.

There have been many studies that have developed games for specific medical conditions. The Fun-Knee is a smart knee brace that pairs with a fishing game application on a smartphone Qiu et al. (2017). In the game, users who have undergone a total knee replacement surgery can improve their range of motion by bending their knee to control the depth of a fishing lure to catch fish. Another study by Ozgur et al. that targets upper-arm rehabilitation created a tabletop maze where a user can physically move a robot through it with their hand to collect points and avoid enemies in a format that is reminiscent of the game Pac-Man Ozgur et al. (2019). These types of devices are effective in overcoming some of the limitations of conventional therapy, but their specific design limits them from being widely adopted.

The commercial video game industry has been rapidly growing over the years Palma-Ruiz et al. (2022). This industry already creates engaging and accessible user experiences. One report found that on average, people play video games 7.6 h per week Severin (2022). Therefore, this research emphasizes utilizing commercial games for rehabilitation. Research by Colder Carras et al. highlighted that many commercial games have shown potential as a therapy for mental health, neurological rehabilitation, psychotherapy, etc. Colder Carras et al. (2018). Other studies have also used commercial games and hardware for physical rehabilitation. However, these studies are usually limited to using games and systems that already have physical motion implemented as a game-play element such as the Microsoft Kinect, Nintendo Wii, Balance Board, or VR headsets Almasi et al. (2022); Marques-Sule et al. (2021); Anwar et al. (2022).

In any game, there is a theoretically infinite number of actions that get mapped to a finite number of buttons based on the system. The complexity of this mapping process can be referred to as control dimensionality (CD) Mustaquim and Nyström (2014). One of our previous studies explored the control dimensionality of different controller types and used that as a basis for designing a new controller for persons with upper limb deficiencies Hassan et al. (2022). Though effective, this process would require creating a special controller for each unique disability or rehabilitation program. Another study categorized commercial controllers by their mapping style Akyaman and Alppay (2021). The four categories were directional mapping (joystick, keypad), kinesic mapping (Microsoft Kinect), incomplete tangible mapping (Nintendo Joy-Con), and realistic tangible mapping (steering wheel). The modular nature of the proposed system aims to provide flexibility for mapping different user movements to in-game actions.

After modifying the hardware and software interface from the design revision stage, a usability study was conducted with 10 students from the University of Tsukuba and 10 medical specialists from the University of Tsukuba Hospital. All the experimental procedures were approved by the University of Tsukuba internal review board (2021R521). Informed consent was obtained from each participant before the experiment.

Each participant was asked to complete three tasks of varying difficulty; easy, medium, and hard. The tasks were written to i) provide a clear goal, ii) have the participant use a different variety and number of sensors each time, and iii) explain the in-game buttons for participants who are not familiar with the controls. To accommodate for any learning effect, each participant was assigned the tasks in a random order. Tasks one and two used Super Mario Maker 2, while Task three used Mario Kart 8 Deluxe. The three tasks are listed below:

1. Make Mario Jump (A Button) using MOTION sensor one attached to your arm.

During the experiment, each participant was recorded using both an external video camera and a screen recorder on the computer. These videos were manually annotated after the experiment to note any complications or errors that the participant made and the time it took to complete the task. The only intervention from the experimenter was to reset the system in between tasks and to offer simple clues or assistance if necessary. The number of times and to the extent to which assistance was provided to the participant was also recorded. The task completion time was measured from the time the participant first flipped over the instructions, touched the laptop, or picked up one of the sensors to the moment that they finished the sensor set-up and clicked on the “Play” tab.

After the participant had completed all three tasks, they were given the System Usability Scale (SUS) to rate their experience with the system. Both the tasks and the survey questions were translated into Japanese with the help of a native speaker for the convenience of the participants. The experimental setup in the University of Tsukuba Hospital can be seen in Figure 9.

The first metric that was used to evaluate the usability of the system was the SUS score. The university students rated the system an average score of 69.25 ± 20.14 while the medical specialists gave an average score of 72.5 ± 17.16. No statistical difference was found between the SUS scores of the two groups.

The second metric to evaluate the usability was the time required by the participant to complete each of the three tasks; easy, medium, and hard. On average, the students took longer to complete the tasks than the medical specialists. These results are shown in Figure 10. Only the hard task showed a statistical difference in the task completion time between the university students and medical specialists (Wilcoxon signed-rank test: p = 0.0039).

All usability experiments were recorded and later annotated for analysis. In addition to any unique occurrences, some common factors were measured for all participants. The first was the number of interventions that were either requested by the participants or provided if the circumstances required it. As there was assumed to be a learning effect as the participants familiarized themselves with the system during the experiment, the number of these interventions that occurred during their first task was also documented. It was also recorded if any participant required multiple interventions per task or the experiment as a whole. The other parameter that was recorded was the number of errors. A mistake is considered an error if the participant is unable to fix it themselves or recognize it before the end of the experiment. This was most commonly forgetting to turn on the sensor or to pair the physical push button in the software. It is possible to turn on the sensors during gameplay and still have them work correctly if the pairing is still done correctly. Therefore, any error that was not able to be corrected during gameplay, i.e., forgetting to pair a sensor completely, was labeled as a critical error and denotes the failure of a task.

Out of the 30 total tasks that were completed, the student group required interventions during six of the tasks and the medical specialists required interventions during 14 of them. Out of these interventions, the number that occurred during a participant’s first task was four for the students and six for the medical specialists. One student participant required multiple interventions during the experiment, while four medical specialists required more than one intervention. Out of the total 30 tasks, 3.33% ended in a critical error for the students and 13.33% for the medical specialists. On average, the medical specialists required more interventions and made more errors than the student participants. The results are summarized in Table 3.

This study aimed to create a modular platform to assist with the gamification of physical rehabilitation. Using the developed hardware and software system, a commercial video game can be controlled by a patient during their rehabilitation. The location and type of sensor can be specified based on the targeted exercise. We also introduced a framework with which to select commercial games that better comply with the needs of physical rehabilitation. The system received an average score of 69.25 ± 20.14 and 72.5 ± 17.16 on the System Usability Scale from university students and medical specialists, respectively. Future improvements are needed to address the issues with the angle sensor and user interface naming conventions before clinical studies begin.