DroidTrainer Mobile Application

Project Type: Interactive

Date: Fall 2009, SI682

Group Members: Adrienne Klum, Chris Wieland, Mukunth Ravi

Skills Applied: Contextual inquiry, Personas & Scenarios, Affinity Diagram, Lo/Hi-fidelity prototyping

Website: DroidTrainer

PROJECT SCOPE

As a semester long project, we designed a fitness application that supports resistance training using the Android mobile platform. This application allows users to set with fitness goals to customize their workouts. Based on the selected fitness goals, users can select from a number of workouts types or exercise by a particular muscle group. Users can log their progress for an exercise or and view statistics that display their progress over time. For project details please check out our project website.

PROCESS

Interviews & Affinity Diagram

Knowing that we wanted to create an Android mobile application related to fitness and health, we constructed a user survey to understand current practices and motivations for being active and for not engaging in physical activity. By method of contextual inquiry, we built an affinity diagram and used the key findings to define the scope of our application.

    Key Findings
  • People have very busy and dynamic schedules which makes it difficult for them to fit recreation into their day.
  • People who do not exercise regularly feel uncomfortable or self-conscious when approaching new forms, exercises, and machines.
  • People need to be motivated to exercise by seeing tangible results not only physically but represented visually as well.

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Personas & Scenarios

After completing the affinity diagram, we design 4 unique personas of varying fitness levels and incentives for using our fitness application -DroidTrainer. Walking through each scenarios helped us flesh out potential features and functionality.

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Lo-Fi/ Hi-Fi Prototypes

We created hand drawn paper prototypes of our interface and tested it with users. Taking the findings from our interpretation sessions we made revisions to our wireframes and then did another round of testing with a high fidelity prototype built in Axure.

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