Evaluating Technology-based Learning Environments

Fall 2020

Research Space

Parkinson affects the capacity for walking, speech, and fine hand movements, the product developed by Beats Medical includes three different modules focused on these disease symptoms. These modules are Mobility, Speech, and Dexterity.

Evaluative Questions

  1. What is the user’s prior knowledge and capabilities in using therapy applications?

  2. Is the BMPT app’s Dexterity features easy to use for users with Parkinson’s disease?

  3. How satisfied is the user after using the Dexterity feature in the BMPT app?

Results

People with Parkinson's Disease are at different stages of their disease. As a result of that, some exercises were challenging for participants with higher stages of Parkinson's Disease to perform the activities set in the mobile application.

Target Audience: People with Parkinson's Disease who experience fine hand movement issues, leading to difficulties with doing up buttons, zippers, or handwriting.

Portfolio Final presentation

Beats Therapeutics designed the Beats Medical Parkinson’s Treat (BMPT) mobile application for people with Parkinson’s disease. To evaluate and determine the validity of the BMPT app, the research team conducted pre-test surveys, usability testing, and semi-structured interviews for data collection. The evaluation questions measured the effectiveness of the mobile application, ease of use, and satisfactory level for the user after using the feature.

Credits: John Osorio Torres, Hasan Sungur, Anasilvia Salazar

Introduction

In today's world, technology has a significant impact on every aspect of life. The smartphone is an excellent example of how technology is involved in our life. We can do many things just by using it. It is used for many purposes in different fields, and the health sector also uses it as a powerful tool. Many health apps improve people's lives. One of them is Beats Medical Parkinson’s Treat, designed for people with Parkinson’s disease.

Parkinson’s Disease (PD) is a neurodegenerative disease caused by a loss of dopamine-producing neurons in a brain region that controls movement. It is characterized by motor and non-motor symptoms that progressively worsen over time. A brief description of these symptoms is provided next, and also in the Appendix.

Beats therapeutic is a company based in Ireland. The principal goal of the products this company develops is to help people with neurological and neurodevelopmental illnesses improve their daily lives through digital solutions. These solutions include different kinds of therapy and learning.

Into the Beats therapeutics catalog of products, solutions for Parkinson's disease, Dyspraxia (DCD), and well-being and relaxation could be found (the last two focused on children). For this project, the Parkinson's product (Beats therapeutic, 2014) was selected. The work consists of an iOS app available for download. This app helps people with Parkinson’s disease to do exercises and keep tracking those. The product also offers a web page to see reports of the performance, user information, and user settings. Information about the product and the target audience can be found in the next paragraphs.

Parkinson affects the capacity for walking, speech, and fine hand movements, the product developed by Beats Medical includes three different modules focused on these disease symptoms. These modules are Mobility, Speech, and Dexterity.

Target Audience

The target audience for this study was people with PD who experience fine hand movement issues, leading to difficulties with doing up buttons, zippers, or handwriting.

The main stakeholders were (1) People with PD, (2) Caregivers, and (3) Physicians and Therapists.

An overview of the experiences of each stakeholder is provided next.

Experiences of people with PD:

Physically: They experience a unique (to every person) combination of PD symptoms, both motor and non-motor (Obeso et al., 2017; Nunes et al., 2016; Paraskevopoulos et al., 2014; Jankovic, 2008). As described by the American PD Association and the National Institute on Aging, the cardinal motor symptoms of PD are:

  • Bradykinesia: Slowness of movement. It often involves difficulty initiating and maintaining movement and performing sequential and simultaneous tasks.

  • Resting Tremor: Involuntary oscillatory movements when the muscles are relaxed. It may be the most easily recognizable feature of PD.

  • Postural Instability: The loss of reflexes of the body to maintain its posture. Normally characterized by gait impairment, easier loss of balance, and others.

  • Rigidity: Increased resistance to the passive movement of the limbs, may be apparent as reduced natural motion or a more “stiff” position of the body.

Mentally: It is more difficult to identify the mental and cognitive implications of the disease, as PD-related non-motor symptoms are not immediately noticeable, and can vary greatly across individuals. Some non-motor symptoms include depression, slowness of thought, difficulty processing visual-spatial information, apathy and others (Rogers et al., 2017; Obeso et al., 2017). Appendix A shows a wider range of motor and non-motor symptoms that people can experience with PD.

Emotionally: Commonly, the subjective experience of people with PD transforms from the moment of diagnosis, often have feelings of denial, resignation, helplessness, embarrassment, acceptance, etc. (Maffoni et al, 2019). Being diagnosed with PD and its implications often results in a life-altering experience, as PD has no cure and symptoms worsen over time.

Goals: Some of the personal goals and aspirations often include, but are not limited to:

  • Amelioration of symptoms

  • Increase understanding of disease and resources to cope

  • Increase autonomy / Decrease the loss of autonomy

  • Support from family, friends, and community

  • Acceptance of condition

  • Maintain physical functions

Pain Points: Some of the notable implications of living with PD result in (Maffoni et al., 2019):

  • Loss of autonomy in daily life

  • Functional decline (motor and cognitive)

  • Slower and more imprecise interaction with objects and devices

  • Impact on self-esteem

  • Resignation

Figure 1 shows a user persona that represents our primary audience: People with PD. This was built using data from the literature on people’s experiences with PD and data from our study.

Experiences of Caregivers:

Caregivers are spouses, relatives, friends, and nurses who provide functional and affective support to people with PD for most of their time. They are the people who spend the most time with people with PD, and their commitment to assist increases as the disease progresses. This in turn leads to frustrations and goals in the caregivers’ experience, some of them are:

Goals:

  • Better understanding of the disease

  • More resources to cope and assist with caregiving duties

  • Community support

  • Role acknowledgment

Pain Points:

  • Caregiver burden (Emotional and Physical)

  • Helplessness towards witnessing disease progression

  • Unaddressed personal needs

Experiences of Medical Specialists:

They are the people who participate in the initial diagnosis and ongoing treatment of people with PD. They commonly consist of General Practitioners, and Movement Disorder Specialists, which is to say, neurologists with additional PD training. Their subjective experience in caring for people with PD is scarcely documented. However, Pinder (1993, 1990) identified a few aspects that describe their role in PD caring:

Goals:

  • Increase scientific knowledge of the disease

  • Understand individual patient’s circumstances

  • Accurately prescribe treatments

Pain Points:

  • Accepting that patients cannot be cured

  • Responding to patients with communication impairments

  • Gauging amount of information to deliver to patient

Figure 1. People with PD user persona

Parkinson's Disease Demographics:

According to a study by Marras et al (2018) with data from across North America, it was ascertained that PD prevalence increases along with age (≥45 yr), making older adults more likely to have the disease. It was also confirmed that PD is more prevalent in males than in females. Appendix B shows a comprehensive infographic describing PD prevalence in the U.S. According to the Parkinson’s Foundation, the projected direct and indirect costs of PD are estimated to be $52 billion a year in healthcare in the United States alone (2020).

Product Description:

The application consists of three main sections with specific exercises to enhance the mobility, speech, and dexterity of the patient. The sections are the following:

Figure 2: (a) Calibration
Figure 2: (b) Steps Per Beat

Mobility

This module is focused on counteracting the mobility symptoms of PD. This module includes a calibration section to determine the best training for walking. (Figure 2 (a)) After the calibration has been done, the user can start the daily treatment for walking. (Figure 2 (b)) The treatment consists of walking at the same rhythm that the beats sound. This therapy is called Metronome therapy. It should be done for 10 minutes twice per day.

Figure 3: (a) Words
Figure 3: (b) Sentences
Figure 3: (c) Ahhhh
Figure 3: (4) Game

Speech

This module is focused on improving vocal volume, intonation, and voice clarity. The module provides exercises and language therapy to do daily. The exercises are Words, Sentences, Ahh, and Game.

The Words exercise consists of speech different words aloud while a measuring needle shows the volume of the speech and the user can adjust the volume to obtain the desired level. Sentence exercise is the same process as words, the difference is that the user should speech a complete sentence rather than just one word. The third exercise is called Ahh, in this, the user should say "aaa" as long as he or she can. And finally, Game, which is an exercise where the user should maintain the balloon floating using her voice volume.

Dexterity

This module is focused on enhancing fine hand movements through a series of exercises based on occupational hand therapies. This module aims to help people with PD be capable of doing essential daily activities such as doing up buttons, zippers, and handwriting. The module includes two different types of exercises: Exercise and Game.

Figure 3: (a) Exercise
Figure 3: (b) Signature Size
Figure 3: (c) Agility

The Exercise section consists of pinch and track a circle and moving it to another smaller circle. The second section is the Game, which includes two types of games. The first one is Signature size, which consists of using a stylus to follow the movement of a moon image, avoiding touching an earth image drawn in the middle of a circle, and moving from top to bottom of the screen. The other game is Agility, which consists of bringing together two circles using the thumb and index fingers.

The project will focus on the Dexterity module, evaluate the different exercises and games of this module, and try-out with end-users to collect evaluative data for analysis to make recommendations for improving the module.

Table 1: Features chart

Description of intended outcomes

From this evaluative study, the intended outcomes are 1) to determine how easy it is to use the app, how satisfying it is to use the dexterity feature, and what knowledge and capabilities users have for using therapy applications; and 2) to develop recommendations around the design of the app based on ease of use, accessibility and compliance with special user interface (UI) design guidelines for people with PD.

The Dexterity module of BMPT aims to help people with PD through in-app exercises, rehabilitating their ability to do up buttons, zippers, handwriting and other fine motor tasks. Moreover, their families and therapists are able to track their treatment using the reports available in the app and in the web page.

Recommendations Preliminary Evaluation

The first evaluation focused on the team’s assessment of user interface design through the combined expertise, therefore, consideration is given to overall quality of visual design and navigation. Further evaluations focused towards the design features impact smartphone interaction for people with PD. For this, the team utilized user interface design guidelines proposed by Nunes et al (2016) as a framework to assess PD-specific usability factors.

The preliminary insights gathered by the team, along with the proposed recommendations were:

  1. Mobile application

    1. It is not designed for all mobile phone operating systems. The application has been designed for iPhones with iOS and it is not available for other mobile phones with Android platform. It would be beneficial to make this app available for Android.

    2. Exiting an activity takes users back to the home page instead of the previous page with a list of activities. This reduced predictability of navigation through the app.

    3. Getting started with the app was confusing when it asked login credentials every time after the app was closed. This could be circumvented by just swiping up/down on the login page, however this option was not clear. One-time login is recommended, especially to reduce task load on people with PD.

    4. It was not clear what the end goal was for each feature. We recommend that each section should contain the explanation about the feature, namely the goals and the expected results from the patient, as well as a time duration estimate.

  2. Currently not every activity is designed with stages of PD progression in mind. Having some levels of difficulty or complexity of exercises would help address this, as well as facilitating adoption by beginner users.

  3. A need for recording and evaluation of the progress of each user is needed within the application. This can be done by adding an evaluation section for each feature, it could be a survey about some daily activities (such as sign, button up) that the patients are able to do after completing the levels. Add a preliminar probing to know what stage of the disease the patient is in, in order to personalize the exercises and measure the patient's improvement after taking these.

Matrix of evaluative questions and instruments of data collection

Beats Therapeutics designed the Beats Medical Parkinson’s Treat (BMPT) mobile application for people with PD. To evaluate and determine the validity of the BMPT app, the research team conducted pre-test surveys, usability testing and semi-structured interviews for data collection. The evaluation questions measured the effectiveness of the mobile application, ease of use and satisfactory level for the user after using the feature. (1) What is the user’s prior knowledge and capabilities in using therapy applications? (2) Is the BMPT app’s Dexterity feature easy to use for users with PD?, and (3) How satisfied is the user after using the Dexterity feature in the BMPT app?

Matrix development process:

The matrix was developed after a series of brainstorming sessions where all the researchers expressed their ideas about the evaluation questions and goals of this project. During that session, six topics were recognized as the main focus of attention for the evaluation project. The topics are:

  1. Need for exercise

  2. Need for an application

  3. Emotions

  4. Knowledge of technology

  5. Fighting through the pandemic

  6. Level of usability for the app

This brainstorming session led to a list of questions, then narrowed down to the following evaluative categories: (1) usability, (2) context information, and (3) user satisfaction. Once the questions were classified into these categories, the team proceeded to discuss and analyzed the data collection methods and selected the most appropriate ones for each goal.

The next paragraphs summarize the reasons to choose the instruments for each category of questions.

Pre-test survey

Context information: A pre-test survey was done to know more about the user's context. With a quick survey, the team collected quantitative and qualitative data about some aspects of the user's daily life relevant to this project, such as habits, activities that imply dexterity and fine motor skills, immersion into technology, and information regarding the changes and challenges faced during this pandemic.

Usability testing

Usability: This technique contains the best instruments of quantitative data regarding app usability. The evaluative questions into the usability category were answered through a usability test. Usability testing allowed the team to measure ease of use, and user satisfaction; all these through the tasks and the System Usability Scale (SUS) questionnaire. This questionnaire was developed by Digital Equipment Co. Ltd and consists of 10 questions formulated to use the Likert scale. The principal advantage of this instrument was that evaluators can convert the general view of a subjective usability assessment, to a quantitative scale to measure it from 0 to 100 points, being 100 the maximum level for usability. As SUS measures the usability from the users' point of view, an heuristic evaluation is intended to be used in order to measure the usability from the best practices perspective. This heuristic evaluation was an appropriate tool to determine if the application fulfills the guides for developing applications for people with PD.

Semi-structured interviews

User satisfaction: Although user satisfaction was measured with the SUS questionnaire, valuable insights could have been missed using one instrument to collect quantitative data instead of one that collects qualitative. To obtain all of these qualitative data, semi-structured interviews were used after usability testing. Interviews allowed the evaluators to formulate the questions based on the user's personal experiences with the app. In order to obtain data from experts about the ease of use and the potential of the application to substitute current alternatives for dexterity improvement, Physical therapists were interviewed as well.

In order to support the validity and reliability of the results, a triangulation in data sources and data collection methods were used. The data sources triangulation included multiple stakeholders' perspectives and permitted the alignment and corroborating of the information collected about the app. The data sources for the triangulation included:

  • People with PD (users, 4 to 6 people)

  • Caregivers (4-6 people)

  • Physical therapists (1-2 people)

The triangulation for data collection methods was possible because of using multiple instruments with different approaches. Quantitative and qualitative approaches were taken to confirm data validity. This triangulation permitted data reliability and helped to eliminate evaluators' biases. The matrix development process is summarized in figure 4. The instruments selected were:

  • Surveys (quantitative and qualitative data)

  • Questionnaires (quantitative data)

  • Interviews (qualitative data)

Figure 4. Matrix Development Process

Pilot test

Preliminary tests with an external participant (without PD) revealed key points for improvement, as well as ideas for optimization in the pre-test survey and usability test protocols:

Survey

  • Must contain fewer open questions and more multiple-choice questions to be more user-friendly to people with PD. Open ended questions were addressed in the interviews.

  • Question 1 - What activities are most important to you? (“enjoy” could be rephrased) Word usage: Meaning of “enjoy” not clear or consistent with options provided.

  • Final questions - Be more clear with what we mean by “new technologies”

Usability Testing

  • Write the username and password in the Task description presentation

  • Add appropriate words to start tasks: Use appropriate wording to give instructions on how to start the Dexterity module. (Homepage on BMPT does not have “dexterity” in it, must to into “Start Treatment” and then view modules)

  • Add initial and final time into the usability testing form, as well as date.

  • Need to brainstorm further: Effective set up a remote usability testing session to properly observe the tasks performed.

Subsequent refinements was delved into developing specific interview protocols for people with PD in the company of their caregivers; and for expert therapists as well. These were not as long as the primary interview for people with PD and served as data triangulation instruments.

Description of the data collection process

Our project's ultimate aim was to examine the impact of the app named Beats Therapeutic, which was used to improve the independence of people with PD through providing activities and short training to improve their hand movements. The first stage of the project was to analyze the efficiency of the app on dexterity. For that purpose, the team conducted a pre-test survey, and investigated the need for an app for dexterity and determine its effectiveness. Before running the pre-test, the team sent a consent form to all participants. After the pre-test, the team used the usability test (usability scale questionnaire) and evaluated different features of the product.After the usability test, the team conducted a semi-structured interview and gathered more profound information about the app's usage and identified the participant's satisfaction with using the app.

Participant Screening/Selection Criteria:

  • Should experience fine motor/dexterity difficulties.

  • Should have a caregiver with them.

  • Should have access to an IOS smartphone. (Apple iPhone)

  • Must feel comfortable using a smartphone/tablet.

  • Must have access to the internet and zoom application.

Evaluation Outline:

  1. Participant Screening

  2. Send selected participants an email

    1. Pre-test survey google form link

    2. Meeting time options

    3. Consent form for recording the video

    4. How to download the app

  3. Schedule individual zoom call

  4. Receive and analyze the pre-test survey responses

  5. Conduct usability testing and record user experience

  6. Conduct interviews and record insights


Data analysis plan

Pre-test Survey

The results from the survey (in Google Forms) were exported as an Excel spreadsheet and the initial analysis was automated. Bar graphs were generated for multiple-choice questions and open question responses were sorted into themes.

Usability Testing

The results from the SUS questionnaire was processed into a final usability score (for impairs items the contribution is the answer minus 1, for pairs the contribution is 5 minus the answer; then multiply the sum of the contributions by 2.5). The result was compared against the average score of 68 to determine how usable the application was. Subsequently, the team conducted a heuristic analysis of BMPT’s dexterity module in reference to UI design guidelines for people with PD developed by Nunes et al. (2016). These guidelines were as follows:

  • Touch interaction

    • Use tap targets with 14 mm or more of side.

    • Use the swipe gesture, preferably without activation speed.

    • Employ controls that use multiple-taps.

    • Use drag gestures with parsimony.

    • Prefer multiple-tap over drag.

    • Adapt interfaces to the momentary characteristics of the user.

  • Information Display

    • Use high contrast coloured elements.

    • Select the information to display carefully.

    • Provide clear information of current location at all times

    • Avoid time-dependent controls

    • Prefer multiple modalities over a single interaction medium (visual & voice interface commands)

    • Consider smartphone design guidelines for older adults.

Semi-structured interviews

The audio recordings from the interviews with people with PD, caregivers and expert therapists was coded according to previously established themes (informed by pre-test survey and heuristic analysis) and condensed into key insights for formative assessments.

Figure 5: SUS vs time using mobile devices per day

Results and findings

Some important findings of the dexterity feature could be found after the data obtained from the usability test sessions were analyzed. Although the sample was very small and heterogenous, the results are valid and reliable. As Sauro (2011) states "SUS has been shown to be more reliable and detect differences at smaller sample sizes than home-grown questionnaires", thereby, the following results can be considered reliable.

The main result obtained from the usability tests is the usability score in the System Usability Scale. The overall usability score for the application's dexterity feature is 73. This score means that the application is just above the average. A score of 68 is considered the average for usability, this based on approximately 500 studies where the SUS was used as the main tool to measure usability (Sauro, 2011). This score shows that the application has a B- in terms of usability, which would represent a 50% of usability if we want to convert the score to a percentage.

One important result to note is the usability scores dispersion. The users that were part of the sample were selected carefully and based on some important characteristics (such as PD, gender equity in the sample, and the same range of age), however, the dispersion of the scores shows a significant difference between the ease-of-use perceived by each participant. The lowest usability score was 40 and the highest was 97.5, which means that for one participant the application is completely unusable and for others is totally usable. After a deep analysis of the qualitative data, a correlation between the number of hours using mobile devices per day and the usability score was found. A value of 0.809 for R^2 explains the discrepancy between usability scores, and could lead to conclude that the ability to use mobile devices (given by the time spent on mobile devices per day) affects the capacity to use the application and the perceived usability. The graph below shows the correlation discussed.

Figure 6: SUS vs time using mobile devices per day

Recommendations

Eliminating or simplifying the authentication-onboarding process: Having a more accessible way of entering the app and getting started is recommended. Participants had significant challenges during onboarding, as they were required to enter username and password, requiring the mobile phone keyboard, which has small buttons that impede accurate data input. This task alone requires entering strings of text, which, regardless of length, can be highly impaired by hand tremors. One participant took 2 minutes to log into the app; another participant took 1 minute. We recommend exploring other methods of user authentication that reduce the physical and cognitive load on users who begin to use the app.

Implement different levels of exercises, according to the stages of PD: The application currently has only one mode of each activity which is not suitable for all applicants, who have different levels of dexterous impairment. Incorporating levels (easy, normal, difficult) can help them customize the application to their needs, generate a progression in training, and further motivate the user to adhere to the exercises.

Add informative details before starting an activity: It is recommended that the app displays a highlight of the goal of each exercise, and time estimation, to inform users of what to expect after they have been instructed by the existing video tutorials. All participants were surprised to know they needed to do the Dexterity Exercise all over again with the other hand after completing it with the first hand. Expectations should be clearly outlined at the beginning of each task.

Implement degrees of error recovery in the games: Some tolerances could be embedded within the pinching exercises to make it easier for users to progress through the exercises. An example of this could be when the circles go off the edge of the screen, they are hard to recover, which puts a halt on the whole exercise until that circle can be retrieved again.

Emphasize linear navigation: In the app, pressing the “back” option takes the user to the home page, instead of the immediately previous step in the sequence of actions. The “back” feature should lead the user to the expected step of the process, in order to reduce confusion of why they returned to the homepage when they wanted to just go a step back.

Findings vs Preliminary Product Critique

When we critiqued the product, we first realized no explicit instruction about how to use the app. We thought that without direct instruction, the learner/user could face difficulties using the app. During the try-out session, many users said they need explicit instruction because, according to most users, the most challenging part of the app is figuring out how to do tasks. Another point that we realized about using the product is there are no different levels of exercise. People with PD have a different level. Some of them are at a high stage of PD. As a result of that, some exercises could be challenging to handle for some of them. During the try-out, some participants who are at a high stage of PD could not do some tasks (exercises) properly. The last thing about the product is that there is no way to recover from errors. When some participants made an error, they had to go back to the main menu, which makes the situation more difficult for them, and it could be very frustrating because they had to start the exercise (game) from the start.

Contributions

John Osorio: Represented the team through the course, recruited participants and participated in primary and secondary research. Moderated usability testing sessions and data analysis.

Anasilvia Salazar: Ana brought in her skills as a computer science expert and helped the team through the process of SUS usability testing. She also equally participated in the brainstorming sessions.

Hasan Sungur: Hasan has contributed in all aspects of the projects. He actively participated during weekly team meetings, while performing data analysis and report writing.

Priyankaa Krishnan: Pri equally participated in the research, documentation and data analysis. She helped proofread the documents, helped design the presentation and post-production of the usability tests.

References:

American PD Association (APDA). Retrieved in September 2020, from https://www.apdaparkinson.org/what-is-parkinsons/symptoms/

Beats therapeutic. 2014. Beats Medical - Parkinson's Therapy Service. Retrieved October 11, 2020, from https://www.beatstherapeutics.com/products/parkinson

Beats Medical - Parkinson's Therapy Service. (n.d.). Retrieved October 11, 2020, from https://www.beatstherapeutics.com/products/parkinson

Jankovic, J. (2008). PD: clinical features and diagnosis. Journal of neurology, neurosurgery & psychiatry, 79(4), 368-376.

Maffoni, M., Pierobon, A., Frazzitta, G., Callegari, S., & Giardini, A. (2019). Living with Parkinson's-past, present and future: A qualitative study of the subjective perspective. British Journal of Nursing (Mark Allen Publishing), 28(12), 764-771.

Marras, C., Beck, J. C., Bower, J. H., Roberts, E., Ritz, B., Ross, G. W., ... & Tanner, C. M. (2018). Prevalence of PD across North America. NPJ PD, 4(1), 1-7.

National Institute on Aging (NIA). Retrieved in September 2020, from https://www.nia.nih.gov/health/parkinsons-disease

Nunes, F., Silva, P. A., Cevada, J., Barros, A. C., & Teixeira, L. (2016). User interface design guidelines for smartphone applications for people with PD. Universal Access in the Information Society, 15(4), 659-679.

Obeso, J. A., Stamelou, M., Goetz, C. G., Poewe, W., Lang, A. E., Weintraub, D., Burn, D., Halliday, G. M., Bezard, E., Przedborski, S., Lehericy, S., Brooks, D. J., Rothwell, J. C., Hallett, M., DeLong, M. R., Marras, C., Tanner, C. M., Ross, G. W., Langston, J. W., Klein, C., … Stoessl, A. J. (2017). Past, present, and future of PD: A special essay on the 200th Anniversary of the Shaking Palsy. Movement disorders : official journal of the Movement Disorder Society, 32(9), 1264–1310. https://doi.org/10.1002/mds.27115

Paraskevopoulos, I. T., Tsekleves, E., Craig, C., Whyatt, C., & Cosmas, J. (2014). Design guidelines for developing customised serious games for PD rehabilitation using bespoke game sensors. Entertainment Computing, 5(4), 413-424. PD. (n.d.). Retrieved from https://www.nia.nih.gov/health/parkinsons-disease

Pinder, R. (1990). What to expect: information and the management of uncertainty in PD. Disability, Handicap & Society, 5(1), 77-92.

Pinder, R. (1992). Coherence and incoherence: doctors' and patients' perspectives on the diagnosis of PD. Sociology of Health & Illness, 14(1), 1-22.

Pinder, R. (1992). Striking balances: detachment or empathy in the management of PD?. Family practice, 9(3), 274-278.

Rogers, G., Davies, D., Pink, J., & Cooper, P. (2017). PD: summary of updated NICE guidance. Bmj, 358, j1951.

Sauro, J. (2011, February 2). MeasuringU: Measuring Usability with the System Usability Scale (SUS). https://measuringu.com/sus/

Schapira, A. H., Chaudhuri, K. R., & Jenner, P. (2017). Non-motor features of Parkinson disease. Nature Reviews Neuroscience, 18(7), 435.

Nunes, F., Silva, P. A., Cevada, J., Barros, A. C., & Teixeira, L. (2016). User interface design guidelines for smartphone applications for people with PD. Universal Access in the Information Society, 15(4), 659-679.