1. Introduction
Nowadays, sedentary lifestyle is increasing due to today’s jobs, which require people to spend considerable amount of time in a sedentary position. A similar observation applies for older adults, especially males, exacerbating their health problems [
1]. The combination of high-calorie food and a sedentary lifestyle causes the increasing rate of obesity and diabetes. Therefore, physical activity is a consistent approach to face these two health problems [
2]. Scientific evidence suggests that physical activity and exercise probably alleviate some symptoms associated with mild to moderate depression [
3,
4,
5]. Consequently, we need new ways to encourage physical activity and to promote better health and well-being [
6]. Therefore, this research aims to design a solution by combining mobile computing technologies to develop a less sedentary lifestyle by promoting physical activities [
7]. Mobile applications are becoming more relevant to help this type of problem since the majority of the population has mobile devices [
8]. Recently, a variety of mobile applications that aim to improve users’ physical condition have emerged and many of them facilitate quick and efficient planning of physical training [
9]. Likewise, there is an increasing number of mobile applications targeting the health domain [
10]. In 2014 between the two leading platforms, i.e., iOS and Android, more than 100,000 mobile applications available are related to the health domain [
11]. This is evidence that the increased use of mobile devices is also stimulating the creation of applications that aim to improve quality of life [
12].
The number of applications for mobile devices associated with the concept of physical exercise and the goal to pursue a healthier daily routine is increasing. Consequently, multiple questions regarding the reliability and integrity of the information and advice proposed by these applications can be established. On the one hand, the scientific validation of the analyzed applications is a crucial requirement for the design and development of reliable mobile solutions to support the physical exercise. On the other hand, it is necessary to understand how mobile applications can promote healthier practices and which are the categories and functionalities provided by these applications. Therefore, this study identifies and presents 36 mobile applications related to personal training.
Figure 1 shows the share of the mobile platforms in the recent years and a forecast of the following years. Currently, the Android operating system has a market share of 86.6% in 2019 and is expected to maintain the same score in 2020. The tendency is to increase since it is predicted that Android will achieve 86.9%, 87.0%, and 87.1% of the global market in 2021, 2022, and 2023, respectively [
13]. Furthermore, the Android operating system is open-source, and mobile applications can be developed using free software, which is supported by Windows, Linux, and macOS. Considering the position of the Android operating system, this study is focused on the existing mobile applications developed for it. Another reason for that is because Android-based mobile devices are generally more affordable than iOS devices, a primary reason why they are more adopted by the young population. At the same time, promoting healthy lifestyles to teenagers is very important because the healthy habits are being developed [
14,
15,
16].
This study’s main contribution is to present a systematic review of the mobile applications that aim to improve the user’s physical condition and pursue a healthy diet [
17]. These mobile applications are related to personal health and personal training and promote a routine of daily exercise and a healthy lifestyle [
18,
19]. The motivation of this paper is related to the development of a mobile application, that must incorporate interaction between personal trainers and users.
This study results in a brief description of all mobile applications, and their objectives in the proposal of exercises by the user’s trainer. In this study, we analyzed 100 mobile applications. Of these 100, several mobile applications were excluded because they do not fit the defined criteria. Our analysis showed that most of the mobile applications used by sports-related users are not scientifically validated.
Another contribution of this paper is to provide a comparison of the actual mobile applications in contrast with the mobile software proposed. Moreover, in this review, it is possible to see mobile applications distributed by categories, so that it is faster to conclude the type of mobile app. Finally, it is possible to understand the purpose of the mobile application development and its existing features.
The mobile applications were chosen considering the keywords “Physical activity”, “Personal trainer”, “Daily plan”, “Fitness”, “Workout”, and “gymnasium”, updated from 2017 to 2020, freely available for download, available on Google Play. We defined a taxonomy after analyzing multiple workout-related applications, that could simplify the development of a mobile application that has relevant features, the main ones being the personal trainer planning the trainee, the visualization of training in the calendar, and a combination between them.
The organization of the remaining sections in this paper are:
Section 2 presents the related work, and
Section 3 contains detailed information and relevant topics about the research criteria.
Section 4 presents the results and goals of each mobile application, and the discussion is presented in
Section 5.
Section 6 concludes the paper.
4. Results
Our review, as illustrated in
Figure 3, identified 100 applications. All the identified applications were checked by reading the description, installing, and testing the app available on the Google Play Store. The evaluation of the mobile applications was made on the number of downloads, update date, and user assessment, resulting in the exclusion of 63 applications after application of the defined criteria. Moreover, after an in-depth qualitative analysis of the 37 applications, one mobile application was excluded since it had been removed from the Google Play store. In the qualitative overview, we included the remaining 36 mobile applications installed and tested.
Following the mobile applications categorized as “Health and fitness”,
Gym Workout Planner [
28],
Gym Fitness and Workout [
29] and
Strong [
43] were the only mobile applications that used the inertial sensors integrated in the mobile device. Calculation of BMI was done in
Fitness Pro Workout Application [
54], and
GymGuide Fitness Exercicios [
42] had a screen to register weight and height and after it presented the BMI to the user. In
GymGuide Fitness Exercicios [
42] it provided the calculation of maximum weight and maximum repetitions for each exercise. Both of them had a list of exercises with video or image and also several types of exercises.
WORKIT [
31],
Gym Workout Plan and Tracker [
32],
Treinos-Workout Trainer [
33],
Treino em Casa para Mulheres [
36],
Academia e Musculação [
40], and
Treinamento Físico [
57] were mobile applications that had a screen that showed statistics of workouts in each day of the week.
Fitness e Musculação [
38] allowed the user to choose meals. According to his goal, the user wanted to lose weight or gain muscle. In the diet area, the food preferences were registered, suggesting the diet plan.
JE FIT—Personal Trainer, Gym, Musculacao Treino [
30] presents exercises for different parts of the body, as well as the plans of each user. For each activity, it was possible to mark the weight, as well as the repetitions. It was possible to visualize the exercise and with the steps for the execution of the activity. In this mobile application, we had a screen that gave access to the 14 days’ statistics. In addition, it was possible to share each training plan.
Home Workout Personal Trainer [
34] has different plans for each goal with videos and images of the different workout technique postures or steps in exercises, and its detailed description. The user can choose the exercise through the part of the body that he/she want to train. It is possible to mark as done the repetitions of each exercise, such as squats, lunges, push-ups, pull-ups, and rotations.
In
Gym Fitness and Workout women: Personal Trainer [
35], it was possible to create routines to achieve a specific goal as well as train with a stopwatch. For each method, the plan was already predefined with a particular time for each exercise. Based on the user’s goal, it was possible to choose which muscle to train, and a list of activities to do. For each of the exercises, it was possible to keep the repetitions made, and the weight used by writing in the mobile application. A dedicated user nutrition screen with advice for the user was displayed.
Gym Coach | Gym Trainer Workout for Beginners [
37] had a predefined training plan for each day of the week. It displayed a list of exercises for the day of the week. Each activity had a video or the presentation of a demonstration image of the practice. In addition, it was possible to change the sets.
Gym App Workout Log and Tracker for Fitness training [
39] had a list of exercises of possible choice to perform the training. There were also training programs already done so that beginners were more likely to start. For each activity, the user had two photographs that exemplified the movement and shows the trained muscles. It had a description to know what to do more in detail. Other essential parts were nutrition and also a graph that showed the progress. It was possible to mark in the calendar through the mobile application.
Gym Workout plan for Weight Training [
41] contained a workout plan in which it showed a list of exercises in which for each activity. There were some pictures with a brief description, as well as the muscle to be trained. There were several types of training plans depending on the purpose of the user for each training plan. This mobile application allowed us to visualize and create an exercise history and personal training programs.
Treino em Casa—Dieta e Personal Trainer [
44] had predefined training plans, with time for each type of program. In the mobile application calendar, it was possible to see the user statistics over time and the days in which there was training. This mobile app provided a BMI calculator. In addition to predefined plans, it was possible to create a plan for greater motivation.
Gym Fitness and workout: Lose Weight, Build Muscle [
45] contained exercise series with pictures, illustrating the muscle to exercise, as well as a description of how to do the exercise. It had several types of activities because of different fitness goals, stretching, bodybuilding, and power-lifting exercises.
In
My Workout Plan—Planeja Treino Diário [
46] it was possible to create the user’s own workout plan, with the repetitions as well as the weight used for the exercise. The user could define which muscle he wanted to practice. It also had predefined plans depending on the level of difficulty, being possible to share with other users.
Gym WP—Academia e Musculação [
47] had a list of exercises, the number of sets made, and the weight used. It had a screen showing the characteristics of the user, weight, BMI, body fat, and the ideal weight it should have. There was a part that was physical evaluation, where the values of the body structure of the user were shown. After the training, it was possible to visualize which muscles were trained, obtaining information on the muscles that would be possible to train the next day. It was also possible to view the history of exercises as well as the graph of progress.
Fitness e Bodybuilding [
48] allowed the creation of an owner or uses predefined plans with different goals, bodybuilding, fitness, or power-lifting. Each workout showed the type of exercise to perform, the repetitions, and how many sets. The user had several images with instructions and a description of what to do and which muscle to train. The images were illustrative, showing the area to be prepared for beginners to have a better choice.
Dr. Training—Fitness e Bodybuilding Gym Workouts [
49] allowed us to choose the type of objective, the type of goal, the muscle to be trained to obtain a list of the exercises. It had animations that demonstrated how to do the exercise. It also had a screen that told us which the best meal to obtain results quickly. Finally, the user had a BMI calculator to know the physical condition of themselves.
Academia exercícios aplicativo 2018 [
50] had plans to train any part of the body, depending on the purpose, such as bodybuilding, fitness, or power-lifting. Each exercise showed an image corresponding to the training with activity details, which muscle it trained, and the practice description.
Slim NOW 2019—Weight Loss Workouts [
51] was a mobile application for physical training for women with different types of difficulty. The user could create a personal training plan, access the physical condition, get the graphs of the calories burned, the weight loss, or gained. It presented the best food to get the best result, depending on the plan that the user wanted.
Gym Generation Fitness and Workout [
52] contained a list of exercises related to the different muscles. In the execution of an activity, an image was displayed that exemplified the training and a description. It had a screen that showed the best power for the desired objective.
Fitness—Diário de Treino e Exercicios, Musculação [
53] offered the possibility to choose the goal to lose weight, build muscle, or be healthy and tone the body. It allowed the choice of the part of the body that it was desired to train and the corresponding exercise. In the activity, there was a video demonstration of the practice and a description of it. It was also allowed to see the history of training, as well as to obtain a report. It was possible to mark the day of the workout on the calendar.
Workout Diary—Training and fitness [
55] allowed the user to save daily exercises, record, and control weight. It was possible to plan the training for the week and observe the results with a graph. It was possible to search for workouts through tags.
Home Workout—Daily Fitness [
56] included several types of training, with several kinds of difficulties. Each type of training had an illustration with a stopwatch. Statistics were displayed using a graph, showing the goals achieved, the results of the day, week, month, or year, the calories burned, as well as the weight statistics. In addition, the mobile application allowed the choice of music by the user.
Daily Fitness—Diet Plan and Weight Loss wWorkout [
58] allowed access and control to the weight and height. Access to food that was made to more easily achieve the purpose of the user. The training had an explanation through text and images.
Treino em Casa sem Equipamento [
59] had predefined exercises for any part of the body, with illustrative videos. Through the built-in calendar, the user could see the days when there were workouts during the training weeks. Each exercise had a video, with pauses between repetitions. The user could see the history of the workout and report that we had access to weight, height, and BMI. He could make and activate reminders in the days of the week that the user wanted.
Exercício de Treino de Ginástica [
60] included specific training, depending on the difficulty chosen and the chosen goal. The exercise had pictures to know how to realize the activity and showed the muscles that were working.
Female Workout Fitness Trainer [
61] allowed us to have defined training, access to recommended food. Each exercise had a description and an illustrative image that showed how to perform the task. The recommended diet had the feeding for the whole day to faster obtain the desired objective.
Fat Burning Workout 2019: Home Weight Lose App [
62] had training plans for several consecutive days. It was possible to choose programs for the desired goal without the need for additional equipment.
Treino em Casa—Sem Equipamentos 2019 [
63] included a list of exercises, for different types of muscles, without equipment. Each workout consisted of a description and a video, with a stopwatch, with the possibility of stopping. It was possible to create personalized training for particular goals.
The results show that most mobile applications had similar functionalities. Around 75% of the applications had a window that had meals for better the user’s eating. In total, 95% of the mobile applications had a division where the user could create personalized training and the possibility of recording the data obtained during the training. Around 55% of the mobile applications allowed the visualization of the training history, performed exercises, and other data related to the activities. Finally, it enabled the user to save them.
5. Discussion
Table 2 presents the user’s evaluation of the reviewed mobile applications. There are two mobile applications with 4.1 stars (5.6%), two mobile applications with 4.2 stars (5.6%), two mobile applications with 4.4 stars (5.6%), 11 mobile applications with 4.5 stars (30.6%), four mobile applications with 4.6 stars (11.1%), four mobile applications with 4.7 stars (11.1%), four mobile applications with 4.8 stars (11.1%), two mobile applications with 4.9 stars (5.6%), and five mobile applications with 5.0 stars (13.7%).
Following the number of downloads, presented in
Table 3, there are four applications with at least 1000 downloads (11.1%), two with at least 5000 downloads (5.6%), six with at least 10,000 downloads (16.7%), four with at least 50,000 downloads (11.1%), seven with at least 100,000 downloads (19.4%), two with at least 500,000 downloads (5.6%), six with at least 1,000,000 (16.7%), four with at least 5,000,000 (11.1%) and one with 10,000,000 downloads (2.7%).
Furthermore, only three mobile applications [
28,
29,
43] (8.33%) use the inertial sensors available in mobile devices, and the remaining 33 mobile applications (91.67%) does not provide direct physical activity monitoring features.
The distribution of mobile applications, according to their updated year, is presented in
Table 4. The update of a significant part of the mobile applications was in 2018, i.e., 11 mobile applications (29.7%), five applications were updated in 2019 (13.5%), 20 applications were updated in 2020 (54.1%), and the remaining mobile application was updated in 2017 (2.7%).
Following the categories of the mobile applications selected, “Health and Fitness” predominate with 35 mobile applications (97.22%), and “Lifestyle” has one mobile application [
60] (2.78%). Several mobile applications allow the user to calculate the BMI that is central to this type of mobile applications, as well as the existence of a sound to know when an exercise starts or ends. Comparing the various features of the reviewed mobile applications, they all have one goal. The proposed objectives can be achieved. However, we found that numerous mobile applications did not have essential features, such as the trainee’s contact with the personal trainer.
Table 5 provides a related work comparison, and it is possible to observe the main objectives studied in the analyzed scientific articles. Additionally, the study [
64] is relative to a mobile application. Therefore it contains some functionalities that the mobile applications studied in this paper do not provide since it can obtain the blood pressure of a specific time. The study includes features that are achievable in the mobile applications considered in the article.
Mobile applications come to also help people with more difficulties in performing exercises, in a more economical and with more motivation [
65]. A personal trainer has an essential role as they provide support as well as training plans for specific goals [
66].
The mobile applications related to physical activity for everyday life are essential due to the possibility of interaction with the personal trainer. If there is no possibility of communication, the application support defined training plans, which after its performance, is communicated to a personal trainer [
67].
Following the results, we classified the reviewed applications into three categories. These categories have been defined according to the purpose and goal of the app, resulting in three types, such as “Health”, “Daily Plan”, and “Physical Activity”.
Table 6 presents the distribution of the mobile applications according to each category.
Approximately 90% of mobile applications contain videos and pictures that help perform the exercise and provide a brief description to complete the explanation. Around 75% have a screen that allows the user to record the results of each activity achieved. In total, 70% of mobile applications do not allow the sharing results. In addition, some of these functionalities offer user access to meal plans. Several mobile applications have limited time for each exercise. That is an exciting feature, since it restricts the user to the time stipulated for each task, thus defining a maximum workout time. On the contrary, the other mobile applications that do not contain this functionality lead to the user specifying the time for each exercise.
For the analysis of the different features, they were grouped in different categories. These are:
Use of sensors: use of sensors to collect physical activity data;
Training plan: definition of the training plan; exercises with images; registration of exercises performed; explanation of the exercises step by step; definition of goals; Definition of time for each exercise;
Nutrition: definition of meals; registration of food preferences; definition of a diet plan;
Weight training: calculation of maximum weight and maximum repetitions for each activity; definition of weight; choose muscle to train;
Personal data: registration of personal data; calculation of BMI;
Social: share training plan; show notifications; reminders;
Statistics: statistics of exercises performed in each day of the week;
Body training: show exercises for different parts of the body; definition of number of repetitions.
Based on the data presented in
Table 7, we can verify that the “definition of training plan”, and “registration of personal data” features are available in all analzyed mobile applications. Moreover, the “exercises with images”, and “registration of exercises performed” features are available in more than 50% of the reviewed mobile applications. Novel mobile applications should include not only all the features described in
Table 7 but also relevant functionalities associated with the real-time communication with the personal trainer, which is not implemented by any of these applications.
Regarding the implementation of notifications, alerts or reminders in the mobile application to control the training of the individuals, only 12 mobile applications (33%) include different functionalities to remember of advice the user for or during training.
Based on [
68], the performance of mobile applications is evaluated by different criteria, such as User Experience (UX) and performance metrics (i.e., load speed, devices and operating systems, screen resolutions, and crash reports), and engagement metrics (i.e., session length and depth, average screens per visit, daily and monthly active users, churn rate, revenue metrics, average revenue per user, purchases, time to first purchase, user lifetime value, conversion rate, and cost per install). In our analysis, we could only evaluate the UX and performance metrics of the identified applications. Firstly, we tested the load speed of all assessed mobile applications, and, as most of them work locally on the mobile device, the load speed is instantaneous. Secondly, we tested the mobile applications with mobile devices with different specifications, since low range to high range, and its performance depends on the memory and power processing of the mobile devices. Thirdly, we only tested the mobile application in the Google Play store (i.e., the mobile application developed for the Android operating system). Fourthly, we examined each mobile application with different screen resolutions between 3.2
and 6.0
, and, in general, the different functionalities are adapted to the different screen resolutions. Finally, even though we asked the mobile application developers for the crash reports of their mobile applications, none of them sent the information. At the same, the remaining indicators only can be accessed by mobile developers.
The analyzed mobile applications provide other functionalities related to promotion of physical activity, such as the indication of a more balanced diet. In these mobile applications, it is possible to verify the increase of the physical exercise, as these applications make the users of the same more motivated to accomplish the activities. These applications aim to make the user attracted by using it, achieving the desired goal. The main functionalities are related to the communication between trainees and personal trainers. In addition, the mobile applications have images and descriptions of each exercise.
On the one hand, several studies support the effectiveness of mobile applications to promote physical activity [
69,
70,
71]. These applications promote a healthy lifestyle in the short term (up to 3 months) [
69]. On the other hand, mobile applications need more in-depth research on the usability requirements and content quality to promote their utilization using the opportunities provided by mobile computing technologies [
72,
73,
74]. These applications must incorporate enhanced methods to promote physical activities daily and techniques to track their usage and consequently sustain their intervention over time.
Since a large part of the population have a sedentary behavior and does not practice physical activity, we conclude that mobile applications related to physical activity can promote people’s health and well-being. Nevertheless, some applications do not have some of the relevant features, making them less motivating for the user. The most important characteristics are the existence of a calendar for the training plans, and several applications do not contain this functionality. Another relevant feature is related to the time limit for each exercise, which means that the training plan has limited time. The most important characteristics were discovered in
Section 4, and its availability in the different mobile application is presented in
Table 7.
Currently, mobile devices support multiple software for enhanced training activities visualization [
75]. Moreover, mobile devices incorporate high-performance processing units that can be used to create training plans according to the user’s requirement [
76]. Therefore mobile computing is playing a significant role in supervising and stimulate healthy activities in people’s daily routines [
77,
78]. Nevertheless, none of the analyzed applications are tested and validated using scientific methods, which leads to an essential research gap for the development of high-quality software to support physical activities [
79,
80,
81,
82,
83,
84,
85]. Mobile devices should be identified as an efficient method to promote and increase physical activity [
17,
86,
87,
88,
89,
90,
91]. Furthermore, mobile devices also have an indirect impact on physical activities since some mobile games are stimulating physical activities using built-in sensors in outdoor environments [
92,
93,
94,
95,
96,
97].
Novel mobile applications to be developed must adapt the training plans to the user. One feature of the methods used to determine user capacity is by calculating BMI, determining their status. The personal trainer should always take this into account, and only after having a reference value can the user prepare workouts. Another relevant functionality is the possibility of commuting between the user and the personal trainer. Additionally, the personal trainer must be able to access the user data and check if the trainee is performing the training as intended. In addition, the existence of training plans in which the user can choose what to do is essential. Furthermore, considering the reviewed features associated with the analyzed applications,
Figure 4 shows a taxonomy where it is possible to observe the characteristics of each category.
Several research review papers on the applicability of mobile applications to support physical activity are available in the literature [
25,
69,
98,
99,
100,
101,
102,
103]. However, these studies do not provide a taxonomy proposal regarding the features used in the analyzed mobile applications. Therefore, when compared with the other review papers available on the literature, this paper presents a taxonomy to classify the analyzed applications into three categories according to the purpose and goal of the mobile app, resulting in three categories, “Health”, “Daily Plan”, and “Physical Activity”. Moreover, these categorizations are also used to classify the reviewed features associated with the analyzed applications.