{"id":7128,"date":"2017-07-08T15:50:31","date_gmt":"2017-07-08T19:50:31","guid":{"rendered":"http:\/\/research.prattsils.org\/?p=7128"},"modified":"2017-07-08T15:50:31","modified_gmt":"2017-07-08T19:50:31","slug":"tracking-fitness-track","status":"publish","type":"post","link":"https:\/\/studentwork.prattsi.org\/infovis\/visualization\/tracking-fitness-track\/","title":{"rendered":"Tracking Fitness – TRACK"},"content":{"rendered":"

Introduction<\/strong><\/h2>\n

Activity or fitness tracking<\/a> was a huge trend in 2016 and now it has become even stronger with an overall aspect of monitoring health. Even sleep and mindfulness has become a big deal with the rise in high-intensity workouts, lunchtime classes and 24-hour gyms. Sleep has never been essential.<\/p>\n

Keeping the upcoming trends in mind, this project aims to be a combination of both information visualization and product development. I developed a hypothetical web based product called \u2018Track<\/strong>\u2019. It is dedicated to making it easier to learn about health and activities. The hypothetical app and website enhance the experience of fitness to empower and inspire the users to live a healthier, more active life.\u00a0\u00a0<\/strong><\/p>\n

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Since, it wasn\u2019t possible to develop an entire app, I focused on highlighting the key fitness visualizations for the users to make tracking health (daily, weekly, monthly) an easy task. My final deliverable is in a low fidelity \u2018website-like\u2019 format which introduces the product and tells the users what it can potentially do.<\/strong><\/p>\n


\nProcess and Rationale<\/strong><\/h2>\n

This project consists of several visualizations which contribute to one story — health<\/strong>. The dataset from which most of these visualizations were created from was acquired from an open data source for visualizations on Quora. Since this is health data which varies from individual to individual, I wasn\u2019t much concerned with the authenticity but on the relations between the data. My primary idea was to generate data myself but since I don\u2019t have prior knowledge it was difficult for me to make comparisons. I finally ended up finding an old FitBit\u00a0data set in Italian from year 2015-2016. After cleaning and translating it on excel, it was ready to use.<\/p>\n

I then used this data to create visualizations on Tableau Public<\/a>. The data set was formatted accordingly. My aim on Tableau was to get the visualizations ready but I wasn\u2019t concerned about placing them on the dashboard because they would eventually be exported to Sketch<\/a> and edited accordingly.<\/p>\n

This project is a combination of visualizations created on Sketch and Tableau. The primary ones were made on Tableau and the supporting ones on Sketch.<\/p>\n

Visualizations on Tableau<\/h3>\n

These visuals were the major charts used to help the users to track and compare data and were derived from the primary activity and sleep datasets.<\/p>\n

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Steps<\/h4>\n

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In order to provide a comprehensive weekly review of the number of steps taken each day, this viz was created using size as the comparative value for the higher number of steps taken each day. The color assigned to steps taken was blue and could instantly be understood by the users to gauge their activity and goals.<\/p>\n

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Calories Burned<\/h4>\n

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Another analysis was the amount of calories burned by the user everyday. This could be viewed either weekly or monthly. To expand on the capabilities of Track, I chose to show a monthly comparison of the viz. The color I denoted to calories burning is red for the users to relate better and make them feel efficient.<\/p>\n

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Activity Gauge<\/h4>\n

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This is one of my favorite visualizations. It gives a month long comparative view of the intensity of activity in minutes pursued by the user. Since it is an overall view, I preferred the users would understand it with a glance. Setting up the colors for each value was the key here\u2014bright red being most intense and bright blue\/green being sedentary and lightweight. The user can get more details about their daily activity by just hovering on it.<\/p>\n

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Number of awakenings<\/h4>\n

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This is an area chart displaying how many times the user woke up during his\/her sleep. The same could be applied to other measure values of rest, actual sleep time etc. But since this is a web-based introduction to the product, I stuck to showing only one.<\/p>\n

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Sleep Gauge<\/h4>\n

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Similar to the Acitivity Gauge visualization, this gives an overall view of the users sleep activity ranging over a month. The user can compare the number of awakenings, minutes of rest, sleep and being awake during the cycle.<\/p>\n

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Comparison \u2013 Activity & Sleep<\/h4>\n

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This Viz presents findings to the user of their activity and sleep patterns on a daily\/weekly\/monthly basis. For this viz, I chose to show a weekly comparison because that is the easiest to understand.<\/p>\n

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Visualizations on Sketch<\/h3>\n

I used sketch for putting together all the information and visualizations in a website like format to introduce the product. Along with this I did mini visuals to support the main visualizations.<\/p>\n

 <\/p>\n

Steps dashboard<\/h4>\n

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This introductory viz is a dashboard like format for mobile devices to help users understand and warm up to the product. The iconography and colors were meant to support the info on the screen and gives them an option to scroll between daily\/weekly\/monthly options (that being the primary feature).<\/p>\n

Another supporting viz\/graphic element is the daily activity gauge just to show to the users that that is also an available option in the results.<\/p>\n

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User Research<\/strong><\/h2>\n

Three users from various backgrounds were recruited to test and provide feedback on the above visualizations. They were chosen carefully on their interest in fitness levels.<\/p>\n

User 1<\/strong><\/p>\n

The first user was someone who is moderately into fitness and uses an activity-tracking app to gauge his performance in marathons etc. His prior experience in using such services led to great feedback on understanding what users actually want to see in these services and how understandable my visualizations were as compared to other apps.<\/p>\n

User 2<\/strong><\/p>\n

My second user was someone who is really into fitness, strength and muscle building but has never used a fitness app. Even though she hits the gym regularly, she doesn\u2019t like running and the concept of fitness tracking is new to her. Her feedback made me see the product and visualizations from a layman point of view.<\/p>\n

User 3<\/strong><\/p>\n

The third user is a data professor who has a lot of experience in studying and analyzing data but doesn\u2019t use fitness apps. His perspective gave me a technical overview of the visualizations and how to convert them into a commercial, user friendly scale.<\/p>\n

Methods of Research<\/strong><\/h3>\n

\u00a0<\/strong>User tests were conducted in either of the two manners-<\/p>\n