# The Digital Footprints on the Run: A Forensic Examination of Android Running Workout Applications
## 1 Introduction  
Nowadays, smartphones and smart wearables are becoming more prevalent and powerful. One of the areas that saw considerable growth with mobile devices is the fitness industry Silva et al. [1], Yeoh et al. [2]. Wearable devices such as smartbands are oriented for fitness purposes as they pack a significant set of sensors, such as heart rate monitor, step counter, Oxygen Saturation (SpO\({}_{2}\)), and sleep monitoring, to name just a few. The functionalities of wearables often depend on and are augmented by smartphones, like, for example, a smartband paired with a specially developed mobile application, communicating through Bluetooth Low Energy (BLE). This companion application interfaces between the device and the smartphone, providing services such as data visualization, geolocalization, access to the Internet for cloud storage and firmware updates. Another crucial role of companion applications is to serve as a bridge between the wearable device and its connected smartphone, facilitating the transfer of fitness data from the wearable to the phone. Subsequently, the phone uploads these data to the application's cloud server. Frequently, a companion application is specifically designed by a fitness brand, making it exclusively compatible with wearables produced by that brand. An example is Garmin Connect ([[https://play.google.com/store/apps/details?id=com.garmin.android.apps.connectmobile](https://play.google.com/store/apps/details?id=com.garmin.android.apps.connectmobile)]([https://play.google.com/store/apps/details?id=com.garmin.android.apps.connectmobile](https://play.google.com/store/apps/details?id=com.garmin.android.apps.connectmobile)) (accessed on 8 August 2024)), which is the companion application for Garmin devices suchas smartbands and smartwatches. Another example is the Fitbit application, which interacts with Fitbit fitness devices. Furthermore, these applications extend their reach and functionality by providing APIs that can be used by independent fitness applications to send/receive data from the associated companion application. For example, through the proper Application Programming Interface (API), the diet application MyFitnessPal ([[https://play.google.com/store/apps/details?id=com.myfitnesspal.android](https://play.google.com/store/apps/details?id=com.myfitnesspal.android)]([https://play.google.com/store/apps/details?id=com.myfitnesspal.android](https://play.google.com/store/apps/details?id=com.myfitnesspal.android)) (accessed on 8 August 2024)) can receive the number of burnt calories from companion applications, providing in return the amount of ingested calories by the users. The Strava ([[https://play.google.com/store/apps/details?id=com.strava](https://play.google.com/store/apps/details?id=com.strava)]([https://play.google.com/store/apps/details?id=com.strava](https://play.google.com/store/apps/details?id=com.strava)) (accessed on 8 August 2024)) application is another example, as it can synchronize data from a running activity tracked by a Garmin smartband. As they often couple precise GPS-based locations with date/time, fitness applications can provide valuable digital forensic data, allowing one to locate the whereabouts of the device bearer at a given date and time [3]. Additionally, if other metrics are available, such as heart rate, it is possible to infer the activity state of the device bearer: idle, normal or high. This might prove of paramount importance in criminal and fraud investigations [4]. An actual illustration of the benefits of smartwatch data in assisting with a criminal investigation is evident in a murder case. The Fitbit data of the victim played a crucial role in securing the husband's conviction, as the Fitbit timeline demonstrated movements within the house and the distance travelled, conclusively placing the husband at the crime scene and refuting his alibi [5].