Atrial fibrillation (AFib) is the most common heart arrhythmia in the world but detecting it can be challenging. For this reason, a detection system consisting of a wearable electrocardiogram (ECG) device, a smart phone application and an algorithm was created. The wearable device was designed to be aesthetically simple yet attractive and be worn either as a necklace or a keychain so that it would always be within reach. The overall usability was also a design goal from the start, requiring the user to only touch the device and start a measurement from the smartphone application with a press of a button. The recorded data was processed with an AFib detection algorithm created based on the Chapman university's database with over 10,000 patients with different heart rhythms. The algorithm is a rule-based detection method, which uses heart rate variability and auto-correlation features. Motion artifacts were also taken into account by using an accelerometer signal measured with the device. The algorithm had an accuracy of 95.3\% for the original database while all of the healthy volunteers (n = 14) tested with the developed system were correctly predicted to have sinus rhythms. The aim is to continue the study by increasing the test set size and to measure ECG with the device from AFib patients.