Abstract
Parkinson's disease (PD) is an incurable, fatal neurodegenerative disease, and only available treatment is to minimize symptoms. Anecdotal evidence suggests whole body workout can help to reduce PD severity; however, it is challenging to quantify its effect on PD. The increased availability of fitness trackers can help in quantifying the effect of whole-body workout on PD. Before using any over the counter fitness tracker, we must study the ease of use of the fitness trackers in PD patients. We interviewed 32 PD patients with six over the counter fitness trackers and determined their perceptions and attitude towards the fitness trackers. Although none of the fitness trackers received perfect scores for ease of use or comfort due to the presence of tremors, two trackers performed significantly better than the others. Further study is warranted to understand the potential for fitness trackers to be used by PD patients.
Introduction
Parkinson's disease (PD) is the second most common neurodegenerative disorder affecting 630,000 people in the US1. PD patients experience motor and non-motor symptoms such as stiff muscles, difficulty in standing, problems with coordination, loss of balance, slow bodily movements, and tremors, which lead to poor quality of life2. Currently, there is no approved therapy to prevent, delay, or reverse the progress of the disease [3]. The most common therapies today are medications to control the symptoms, but they do not prevent or slow the progression of the disease4,5. In recent years, alternative therapies involving activity-based approaches such as whole-body workouts, forms of rigorous physical exercises such as dancing and non-contact boxing, have been shown to have a positive effect on patients with PD6-9. However, it is unknown how and to what extent whole-body workouts operate to slow or stop PD progression. One of the biggest challenges to conducting research in this domain could be the difficulty in recruiting patients (small sample size), the progress of the condition, and the effect of interventions10-12. Both clinicians and researchers typically use biophysical tests such as an electroencephalogram (EEG) to monitor disease severity and measure changes in motor and cognitive function [13-16]. These tests can only be administered by qualified technicians in a clinical facility, which is time-consuming, tedious, expensive, and labor-intensive [17]. The lack of a low cost, easy to use, continuously monitoring, standards-based means of measuring the motor function status, and progression of PD is a major hindrance to both improved management for PD patients and a constraint on research18,19.
In the last decade, the use of fitness trackers/sensors such as Fitbit, Apple watch, and Jawbone by the general public in the US has become very common [20,21]. Each of these trackers/sensors contains an accelerometer that can record variations and intensity of movement. If this motion data can be interpreted to express the progression of PD and the effect of interventions, then these trackers/sensors may be useful and cost-effective for the large-scale monitoring of patients' exercise intensity and for quantifying the effect of exercise on PD progression. However, it's unclear the extent to which these trackers/sensors will be adopted and used continuously by PD patients due to the presence of motor symptoms such as tremors, which may make them uncomfortable or difficult to use [22,23]. From here on, we will refer "fitness trackers/sensors" as "trackers".
Based on our literature review, most of the existing studies focusing on the ease of use of over-the-counter fitness trackers are in people who do not have PD24-28. For instance, Ridgers (2018) performed a study on the usability and acceptability of fitness tracker use among Australian young adolescents and found the Fitbit Flex was the easiest to use activity tracker for tracking the activities29. Similarly, Chaparro et al. investigated the usability of six activity trackers among 19 individuals and found that Fitbit and Garmin were the most popular trackers among the participants because of its lightweight and digital display30. While Rasche et al. studied the age-related usability of an activity tracker, authors found that the younger and older age groups used the activity tracker without difficulty independently without any specific training31. From these studies, we can conclude that there is some evidence showing that certain trackers work better than others for some users in specific circumstances; however, there is no study demonstrated the ease of use of over the counter trackers in PD patients.
The long-term goal of our research is to identify the best fitness trackers that will be highly adapted by the PD patients and to develop algorithms that allow researchers, clinicians, and patients to monitor activities, including whole body workout. Our short-term goal is to compare and evaluate the ease of wearability of several popular models of fitness trackers for PD patients in the presence of motor symptoms. Because of the limitations in dexterity associated with PD, limited our scope to basic functions such as putting on, taking off, and simply wearing these specific fitness trackers. We consider these attributes to be gating important factors before considering ease of use in the more complex device functions (industrial design of the device, and ergonomic aspects). The results of this study would determine the ease of use, attitude, and perception of six popular over the counter fitness trackers in patients impaired with PD and answer if over the counter fitness trackers could be used to quantify the effect of whole-body workouts in PD patients.
Methods
First, we identified six popular, commercially available trackers for which the manufacturer's marketing documentation indicated they had functions and features valuable to track activities in patients with PD. Second, we recruited 32 PD patients onsite (from here on referred as participants) with various levels of PD severity through Rock Steady Boxing gymnasium in Indianapolis, Indiana. Rock Steady Boxing is a nonprofit organization that offers non-contact boxing-based fitness activities (a form of whole-body workout) for patients with PD. We asked these participants to perform basic functions such as putting on and removing the fitness trackers and performing certain tasks while wearing the selected trackers. Next, we asked them to complete a survey of their perceptions and attitudes towards fitness trackers. Finally, we analyzed the results to determine which of these trackers the PD patients would be most likely to wear and use on a continuous basis.
Commercially available fitness trackers
We began our study by identifying the functions and features that were the most valuable to PD patients such as GPS, activity identification, touch, water resistance, sound, sensor, heart rate, exercise tagging and such as. We selected six trackers that had the most features in line with our feature list (feature list of 27 features). Included trackers in this study are: 1) Tracker A = Fitbit Blaze Large Black (2016 model); 2) Tracker B = Xiaomi Mi Band Black (2014 model; 3) Tracker C = Fitbit Flex Wireless Activity + Sleep Wristband Black (2013 model); 4) Tracker D = Jawbone UP2 Silver (2015 model); 5) Tracker E = Pebble SmartWatch Red (2016 model); 6) Tracker F = Pebble Steel Smartwatch Stainless (2014 model).
Survey design
Since this is a first study to assess the feasibility of wearing commercially available fitness trackers by PD patients, we developed our own survey questions without incorporating survey questions from the previous studies. Two of the team's members who are clinical informaticists developed these survey questions. Detailed information about the survey questions is described in Table 1. To make sure the survey questions are easy to understand by respondents who are unfamiliar with healthcare domain, we recruited two external reviewers to validate the survey. We asked them to evaluate the survey for question flow, sentence organization, grammar, and ease of understanding. The resulting survey scored very high (0.86) on Cohen's Kappa statistical test for agreement among the reviewers32.
Table 1: Questionnaire to assess the feasibility of wearing fitness trackers in PD patients.
| Survey Questions | Survey Response Options |
| 1: What is your age group? | < 35 years, 36-45, 46-55, 56-65, 66-75, 76-85, > 85 years |
| 2: How long did it take for you to put on and wear your device? (seconds) | /Open-ended |
| 3: How long did it take for you to remove your device? (seconds) | Open-ended |
| 4: How easy was it to wear your fitness device? | Very easy, Easy, Moderate, Hard, Very Hard, Other |
| 5: How comfortable did the material feel against your arm? | Comfortable, Moderate, Rogh/Uncomfortable, Other |
| 6: How comfortable is it to carry the device while working out? | Comfortable, Moderate, Rough/Uncomfortable, Other |
| 7: How likely is it that would start to use/continue using this device? | Very likely, Maybe, Never, Other |
| 8: How did Rock Steady Boxing help you? | Open-ended question |
| 9: How long have been attending Rock Steady Boxing? | Open-ended question |
| 10: How often do you come to Rock Steady Boxing? | Open-ended question |
Data collection
We recruited participants from PD patients who are regular members in therapeutic exercise programs at Rock Steady Boxing. We used flyers to recruit participants. The 32 participants recruited for our study suffered from a wide range of disease intensities. None of the study participants had previously used fitness trackers. Each of the 32 participants was invited to work with all six of the fitness trackers. The order of the trackers was changed between participants to reduce the bias that comes with an increased general familiarity with using this type of devices. We verbally asked them to do the tasks like putting the tracker on and off and asked them questions regarding their experience with the trackers. We collected information about the initial impression of trackers, ease of use (the ability of the patient to put on and take off the device without hindrance or difficulty), comfort (see questions 4 to 6), and overall likelihood (see question 7). We also collected information on how long and how often they have been attending the Rocksteady boxing facility (see questions 9, 10). We asked the questions 9 and 10 for our future study to find out how rigorous physical activity can help reduce PD progression. Due to the presence of tremors, we (all authors) noted down each response on paper and then transferred the information in a computer for further data analysis.
Statistical Analysis
To measure if there was an overall difference in opinion within the six different trackers for Questions 4-7, a nonparametric repeated measures omnibus analysis called the Friedman's test was conducted for each question. Each fitness tracker was compared to the other fitness trackers to determine individual preferences for Questions 4-7, using a pairwise Wilcoxon Signed-Rank test. A Bonferroni adjustment was applied to the overall statistical significance to prevent the accumulation of Type I error and control for the familywise alpha level when conducting individual pairwise tests for p-values. The formula given to provide the Bonferroni adjusted p-value was a' = 1–(1-a)1/k with a' representing the adjusted critical p-value from the adjustment, a representing the standard Type I error of 0.05, and k representing the number of multiple comparisons made which was a total of 15 comparisons for this study. Any p-value that was below the adjusted critical p-value was considered statistically significant. Summary and descriptive statistics on the time to wear and remove the trackers were performed for Questions 2 and 3, and comparison of these time measurements was analyzed using the Kruskal-Wallis nonparametric ANOVA test. The default level of significance was compared at α = 0.05 for all analyses with the adjusted α = 0.00341 for Questions 4-7 due to the multiple comparison tests and Bonferroni correction. All statistical analyses were performed using SAS® software version 9.4.
Results
Age of the participants
All of our participants were older than 45 and younger than 86 years of age. Three participants (9.4%) were between 46-55 years old, nine participants (28.1%) were between 55-65 years, and two participants (6.3%) were between 75-85 years. The 65-75 age group was the largest cohort in the study, with eighteen participants representing 56.25% of our sample.
Initial impression
Although all 32 participants were given the opportunity to use all six fitness trackers, none of the participants chose to test all six devices. The reasons why participants declined to try a fitness device included: the fitness tracker did not fit ("the band is too short"); the participants didn't like either the attachment mechanism (such as a buckle), or the look or feel ("this one is 'too heavy' or 'clunky"). In calculating our scores for each device, those that were selected more often received higher scores than those which the participants declined to try at all to use. Of the six fitness trackers, 28 people tested tracker E and 29 tested tracker F, compared to only 11 people who chose tracker C and 12 who chose tracker D. Trackers A & B were tested by 22 participants.
Ease of use
We defined ease of use as the ability to put on and take off the device without hindrance or difficulty. We evaluated ease of use by measuring the amount of time in seconds that it took for a subject to both wear and take off a fitness tracker. For each fitness tracker, we calculated the mean and median times to put on or take off the fitness tracker along with the standard deviation, the lowest (shortest) time, and the highest (longest) time. We also noted the number of participants that declined to test each fitness tracker. Table 2 shows the results of the two ease of use questions.
Table 2: Summary statistics of time to put on and take off the fitness tracker.
| Question 2: How long did it take for you to put on and wear your device? (seconds) | ||||||||
| Tracker | Samples | Mean | Median | Std Error | Std Dev | Lowest | Highest | Other |
| A | 22 | 27.2 | 22.5 | 2.717 | 12.7 | 4 | 58 | 10 |
| B | 22 | 31.5 | 26.0 | 3.924 | 18.4 | 9 | 74 | 10 |
| C | 11 | 41.1 | 51.0 | 8.940 | 29.6 | 9 | 100 | 21 |
| D | 12 | 52.3 | 48.0 | 7.431 | 25.7 | 14 | 100 | 20 |
| E | 28 | 21.3 | 20.0 | 1.751 | 9.2 | 8 | 45 | 4 |
| F | 29 | 11.6 | 8.0 | 1.496 | 8.0 | 3 | 30 | 3 |
| Question 3: How long did it take for you to remove your device? (seconds) | ||||||||
| Tracker | Samples | Mean | Median | Std Error | Std Dev | Lowest | Highest | Other |
| A | 22 | 23.1 | 15.0 | 4.572 | 21.4 | 5 | 100 | 10 |
| B | 19 | 20.7 | 12.0 | 5.277 | 23.0 | 2 | 80 | 13 |
| C | 7 | 15.0 | 9.0 | 7.432 | 19.6 | 2 | 58 | 25 |
| D | 9 | 27.6 | 25.0 | 7.106 | 21.3 | 5 | 64 | 23 |
| E | 27 | 16.0 | 10.0 | 2.746 | 14.2 | 3 | 48 | 5 |
| F | 28 | 9.4 | 6.5 | 1.583 | 8.3 | 2 | 38 | 4 |
Using the Kruskal-Wallis test, there was an overall statistically significant difference in the distribution of time to put on the fitness trackers (χ2(5) = 49.1619, p < 0.0001) and to take them off (χ2(5) = 15.8928, p < 0.0072). Tracker F had the lowest (quickest) mean and median times, followed by Tracker E for question 2, putting on the tracker, and Tracker C for question 3, removal. Tracker D had the highest meantime, and Tracker C had the highest median time putting on the fitness tracker. With respect to removal time, Tracker F had the lowest (quickest) mean and median time, while Tracker D had the highest (slowest) mean and median time.
Comfort
Although not every participant was able to put on a fitness tracker by him/herself, some participants were able to wear the fitness trackers with assistance putting them on and taking them off. Hence, the number of people who responded to questions about comfort may be greater for some fitness trackers than those who could put on or remove the fitness trackers independently. Table 3 displays the number and percentage of participants responding to an opinion level for each tracker for Questions 4-7, while Figure 1 represents the same information in bar charts.
Table 3: Frequency tables and proportions of responses for Questions 4 through 7 (asks about the comfort and the likelihood of continuing to use the tracker over the time).
| Question 4: How easy is it to wear your fitness device? | ||||||
| Opinion Level | Tracker A (%) | Tracker B (%) | Tracker C (%) | Tracker D (%) | Tracker E (%) | Tracker F (%) |
| Very Easy | 3 (9.3) | 5 (15.6) | 1 (3.1) | 1 (3.1) | 11 (34.3) | 16 (50.0) |
| Easy | 4 (12.5) | 2 (6.2) | 1 (3.1) | 2 (6.2) | 7 (21.8) | 8 (25.0) |
| Moderate | 7 (21.8) | 4 (12.5) | 4 (12.5) | 1 (3.1) | 4 (12.5) | 0 (0.0) |
| Hard | 3 (9.3) | 7 (21.8) | 1 (3.1) | 4 (12.5) | 2 (6.2) | 0 (0.0) |
| Very Hard | 4 (12.5) | 5 (15.6) | 9 (28.1) | 7 (21.8) | 3 (9.3) | 0 (0.0) |
| Other | 11 (34.3) | 9 (28.1) | 16 (50.0) | 17 (53.1) | 5 (15.6) | 8 (25.0) |
| Question 5: How comfortable did the material feel against your arm? | ||||||
| Opinion Level | Tracker A | Tracker B | Tracker C | Tracker D | Tracker E | Tracker F |
| Comfortable | 10 (31.2) | 9 (28.1) | 3 (9.3) | 5 (15.6) | 21 (65.6) | 11 (34.3) |
| Moderate | 7 (21.8) | 5 (15.6) | 6 (18.7) | 7 (21.8) | 4 (12.5) | 6 (18.7) |
| Rough | 4 (12.5) | 4 (12.5) | 2 (6.2) | 3 (9.3) | 1 (3.1) | 12 (37.5) |
| Other | 11 (34.3) | 14 (43.7) | 21 (65.6) | 17 (53.1) | 6 (18.7) | 3 (9.3) |
| Question 6: How comfortable is it to carry the device while working out? | ||||||
| Opinion Level | Tracker A | Tracker B | Tracker C | Tracker D | Tracker E | Tracker F |
| Comfortable | 12 (37.5) | 9 (28.1) | 2 (6.2) | 4 (12.5) | 17 (53.1) | 11 (34.3) |
| Moderate | 1 (3.1) | 8 (25.0) | 5 (15.6) | 6 (18.7) | 7 (21.8) | 7 (21.8) |
| Rough | 7 (21.8) | 3 (9.3) | 8 (25.0) | 5 (15.6) | 2 (6.2) | 9 (28.1) |
| Other | 12 (37.5) | 12 (37.5) | 17 (53.1) | 17 (53.1) | 6 (18.7) | 5 (15.6) |
| Question 7: How likely is it that would start to use/continue using this device? | ||||||
| Opinion Level | Tracker A | Tracker B | Tracker C | Tracker D | Tracker E | Tracker F |
| Very Likely | 2 (6.2) | 5 (15.6) | 0 (0.0) | 1 (3.1) | 17 (53.1) | 10 (31.2) |
| Maybe | 1 (3.1) | 2 (6.2) | 0 (0.0) | 0 (0.0) | 1 (3.1) | 4 (12.5) |
| Never | 2 (6.2) | 3 (9.3) | 2 (6.2) | 7 (21.8) | 0 (0.0) | 1 (3.1) |
| Other | 27 (84.3) | 22 (68.7) | 30 (93.7) | 24 (75.0) | 14 (43.7) | 17 (53.1) |
Figure 1.
Graphical representation of participants' responses to Questions 4 through 7 (asks about the comfort and the likelihood of continuing to use the tracker over the time).
For Question 4, "How easy was it to wear your fitness device?" 75% of the participants reported that Tracker F and 56% of Tracker E was easy or very easy to wear, compared to less than 22% for each of the other fitness trackers (n=4). There was an overall statistically significant difference in opinions using Friedman's test (χ2(5) = 41.7008, p < 0.0001). As depicted in Table 4, the Wilcoxon Signed-Rank tests showed that Tracker E (p < 0.0001) and Tracker F (p < 0.0001) was significantly different from both Tracker C and Tracker D in terms of easiness of wearing the device. Tracker B was different than Tracker C (p = 0.0008) and Tracker D (p = 0.0002). There was no statistical difference in opinion among Tracker A users compared with other trackers. Overall, favorability was higher for Tracker F followed by Tracker E for this question.
Table 4: Wilcoxon multiple comparison p-value denotations between trackers*.
| Tracker Comparison | Question 4 | Question 5 | Question 6 | Question 7 |
| A vs B | 0.9 | 0.4 | 0.8 | 0.2 |
| A vs C | 0.0 | 0.0 | 0.0 | 0.1 |
| A vs D | 0.0 | 0.0 | 0.0 | 1.0 |
| A vs E | 0.0 | 0.0 | 0.0 | 0.0 |
| A vs F | 0.0 | 0.2 | 0.2 | 0.0 |
| B vs C | 0.0 | 0.0 | 0.0 | 0.0 |
| B vs D | 0.0 | 0.2 | 0.0 | 0.1 |
| B vs E | 0.0 | 0.0 | 0.0 | 0.0 |
| B vs F | 0.0 | 0.1 | 0.3 | 0.2 |
| C vs D | 0.8 | 0.2 | 0.3 | 0.0 |
| C vs E | <.0001 | <.0001 | <.0001 | <.0001 |
| C vs F | <.0001 | <.0001 | 0.0004 | <.0001 |
| D vs E | <.0001 | 0.0009 | 0.0 | <.0001 |
| D vs F | <.0001 | 0.0 | 0.0 | 0.0021 |
| E vs F | 0.4 | 0.0 | 0.2 | 0.3 |
Shaded values represent statistically significant p-values according to the Bonferroni adjustment critical p-value at a = 0.00341
Results from Question 5 "How comfortable did the material feel against your arm?" show that Tracker E had the most respondents stating that the tracker was comfortable (65.63%) while Tracker A (31.25%) and Tracker F (34.38%) showed some favorability but at a lesser percentage. However, Tracker F had a slightly higher percentage of participants saying that the tracker was rough against the arm (37.50%). Furthermore, Tracker C (65.63%) and Tracker D (53.13%) had the highest participants saying "Other" as their response. Using the omnibus Friedman's test, the overall opinions of comfortability against the arm among the six trackers were statistically significant (χ2(5) = 31.4100, p < 0.0001). Tracker C showed a statistically significant difference compared to Tracker A (p=0.0013), Tracker E (p < 0.0001), and Tracker F (p < 0.0001) while Tracker D was different than Tracker E (p = 0.0009). Overall, Tracker E scored highly in comfortability when worn against the arm over all the other devices.
For Question 6 "How comfortable is it to carry the device while working out?" results show that Tracker E had the most responses for comfortability (53.13%) while Tracker A (37.50%) and Tracker F (34.38%) showed some favorability but at a lesser percentage. Similar to Question 5, Tracker F had a moderate response rate for roughness (28.13%). Roughness was also found for a quarter of the respondents for Tracker C (25.00%). Among the "Other" opinion category, Tracker C (53.13%) and Tracker D (53.13%) had the same percentage of participants answering this response. The overall difference in comfortability when carrying the device using Friedman's test was statistically significant (χ2(5) = 26.2207, p < 0.0001). Similar to results for Question 5, Tracker C showed a significant difference compared to Tracker E (p < 0.0001) and Tracker F (p < 0.0001) while Tracker D showed a difference compared to Tracker E (p = 0.0017). In summary, when comfortability in carrying the device was taken to account, Tracker E outperformed all other trackers.
Overall likelihood
Question 7 "How likely is it that you would start to use/continue this device?" provided results that showed Tracker E having the highest percentage of respondents saying they were very likely to use the tracker among all our trackers studied (53.13%). However, there was a moderate percentage of participants who stated "Other" for the same tracker (43.75%). Overall, the percentage of participants saying "Other" for this question was very high for all trackers. No participants preferred Tracker C while a sizable percentage stated they are not willing to wear Tracker D (21.88%). The overall Friedman's test was found to be statistically significant (χ2(5) = 34.3140, p < 0.0001). Tracker E (p < 0.0001) and Tracker F (p < 0.0001) was significantly different than both Tracker C and Tracker D. Additionally, Tracker A was found to be significantly different than Tracker E (p < 0.0002). From this analysis, there is a higher preference in using Tracker E and to a lesser extent Tracker F over the other tracking devices.
Discussion
We sought to identify trackers that demonstrate the best ease of use, comfort, and favorability (likelihood of continued use) among PD patients. Overall, Trackers E and F received the highest favorability while Trackers C and D received much lower favorability. The results suggest that each fitness tracker is different in terms of ease of use, comfort, and favorability among PD patients but that none stood above the others on all measures. Tracker E is the most comfortable to wear and is the model most likely to be worn over an extended period of time. Tracker F was not as comfortable against the arm while working out compared to Tracker E. Trackers A and B scored the lowest on ease of use but were only marginally more comfortable. Additionally, if a tracker was found to be highly comfortable against the arm, the tracker was also likely to be comfortable when worn during exercise activities. This is shown in Figure 1 where the distribution of responses among the six trackers in Question 5 was similar to Question 6. This may indicate that different measures of comfortability of the tracker might not all be that different from each other.
For the quickest time necessary to wear the device, Tracker F performed the best overall and had the most participants successfully putting on and taking off the device. This finding was highly reflected in the results from Question 4 on the survey on the ease of use. Conversely, Trackers C and D took longer for the participants to put on the device and had the lowest number of participants who could successfully put on the device. Trackers C and D also had the smallest number of participants say that the tracker was easy to use. However, despite Tracker C having the longest time to put on the device, the removal time was the second quickest among the other trackers. The reason behind this was the design of the tracker's wristband which had a "lock within the hole" mechanism that made it harder to put on but easy to remove. Patients had to put the device on their arm and then push the device button located on the band into the hole to completely attach and lock it. However, for participants with more tremor, it was extremely difficult for them to put it on. In fact, some patients gave up trying to put the fitness tracker on because it was too difficult. However, removing the device was quick because it took only one pull to disengage the lock.
Further investigation may posit that the form or method of the tracker being worn may prove significant as some trackers may have replaceable straps, Velcro, or capable wristbands. Some wristbands may be difficult to wear or put on the wrist but are easily removed and vice versa. Recommendations on the best fitness tracker for PD patients should consider how the device can be worn appropriately and easily without limiting the physical activity of the wearer.
To minimize the effect of sponsor bias, we masked the brand names of all six trackers used in the study and referred to each tracker with alphabetical names. Our participants represented PD patients at all stages of the disease and symptom progression. Therefore, our results are not biased towards patients at any particular stage in the disease or symptom progression. Most of the patients have not used any fitness tracker devices as all the trackers were new to them. Some of our questions were open-ended so that participants could freely express their opinions without having strictly defined options for answer choices.
Existing studies on wearable devices mainly focused on product design specifications and user-interface applications. Several reviews on wearable devices appearing on internet web pages have different opinions which are often subjective and lack experimental results to evaluate the type of participants and the accuracy of information on the devices. For example, a study was performed on "comparison of wearable fitness devices" where the authors focused on both subjective and objective data irrespective of manufacturer's claims to compare the user's satisfaction, user-friendliness, and accuracy of data collected and managed among four commercially popular fitness trackers, namely Fitbit Flex, Withings Pulse, Misfit Shine, and Jawbone33. This study reported that Misfit Shine scored the highest for its design and hardware features in contrast to Withings Pulse which was recommended by the highest number of participants for its user-friendliness, accuracy in activity tracking, and satisfaction levels among all the devices they tried. Furthermore, the study acknowledges that the design and the technology together are on the same levels to evaluate the quality of tracking devices both objectively and subjectively. In another study, the acceptance of wearable trackers (Fitbit Zip, Jawbone Up 24, Misfit Shine, Withings Pulse) is tested in participants with chronic illness. The study concluded that Fitbit Zip secured the highest mean acceptance score of 68 although having negative feedback that it is too short to put on and a mean acceptance score of 65 for Jawbone despite having positive comments on its design and ease of wearing34. Most of these studies compared the wearable trackers based on their design characteristics or user-interface applications. But there is no such study which can tell us about the ease of use and comfort while wearing these devices in patients with PD because patients are suffering from symptoms such as muscle rigidity, tremors, problems with muscle coordination and balance pose difficulty in wearing the trackers by themselves. This prevents them to choose a wearable tracker for long-term usage that could possibly affect the intervention to track the disease progression. Users are often compromising these behavioral characteristics for other reasons such as the cost of the device and features or applications the device provides for tracking the activities.
Limitations and future work
Our study was limited to 32 participants from a single organization, which may not be a large enough sample to achieve statistically valid estimates of patterns to answer our questions and generalize the entire US population. In the future, we will increase our sample size by recruiting more patients from the different locations of Rock Steady Boxing and different organizations to conduct a study which may be able to provide more generalizable results. Second, we did not stratify our subject population by stage of progression or severity. It may be that people at different stages or levels of severity may react differently with respect to ease of use and comfort. In the future, we will categorize the patient population by the PD severity and examine their perception and attitude towards these fitness trackers. Third, our study looked only at the ease of use and comfort of the trackers without considering the potential value of new information that might benefit the subject in his or her management of their PD condition. It could be that those reactions that are perceived as barriers to ease of use or comfort initially may be less important once the subject sees the value of the information. Finally, patients were exposed to the fitness for a short duration of time. Therefore, the exposure to the trackers was relatively short. In the future, we will expand our study to examine the use of these trackers in daily life and identify the most popular tracker among patients impaired with PD. For the next step, we propose to use fitness tracker E and F to collect raw data of patients impaired with PD while they perform the exercise. We will use this raw data to develop algorithms that can identify the type of exercise (dancing, boxing, etc.), and its intensity. Using this information, we will evaluate its impact on PD progression. We will also consider other factors towards the user adoption such as battery life, Bluetooth syncing, and mobile applications. Future work should also include the involvement of PD patients in the long-term design acceptance and functional capabilities of exercise management programs to enhance adoption rate.
Conclusions
Owing to the recent advancements in devices designed specifically to measure motor function, commercially available fitness trackers play a key role in tracking the physical activities that could determine PD progression. Our study demonstrated the ease of use and comfort of various commercially available wearable trackers in PD patients. We conclude that commercially available fitness trackers should be considered as an alternative to dedicated devices or other devices that could be adapted for this purpose. Moreover, while none of the fitness trackers received high scores in all areas, at least two fitness trackers, E and F, received significantly higher positive responses than others while two fitness trackers, C and D, performed significantly worse. Therefore, we conclude that further study is warranted to look more closely at the design and use of fitness trackers for PD patients.
Internal Review Board
This study was approved by the Internal Review Board at Indiana University Purdue University Indianapolis (Protocol approval # 1512203933).
Acknowledgments
The authors wish to thank the Rock Steady Boxing Team, Indianapolis, for their cooperation and Parvati Menon, a graduate student at the School of Informatics and Computing, Indiana University Purdue University Indianapolis, for her support.
Author Contributions
All the authors contributed equally to the development of this work.
Conflict of Interest
The authors report no conflicts of interest relating to this work.
Figures & Table
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