2. State of the art
Advances in the miniaturization of (inertial) sensing technology, along with the increasing availability of smartphones
as a sensing platform, have given rise to many commercial appliances, apps, and general academic interest into people’s
physical activity. This allows for embedded interaction [3], that is to look at new opportunities and application areas that
arise for interactive systems and at novel ways for human–computer interaction (HCI) enabled thereby.
Beyond straightforward applications in medicine, where physical activity has to be quantified reliably, many lifestyle,
sports and professional assessment systems have been developed. This section first explores systems that employ inertial
sensors to assess different aspects of physical activity. Subsequently, the landscape of (commercial and free) health and
fitness applications on smartphones is summarized in a comparative study.
2.1. Automatic assessment of physical activity
Body-worn and pervasive sensors have been employed in a large variety of recognition scenarios, identifying different
types of physical activities [4–8] with satisfying accuracy. Quantifying qualitative aspects of human motion, such as motor
performance, has been of intense focus in medicine, where particularly the assessment of degenerative conditions such as
Parkinson’s disease is of interest [9,10]. Automated skill assessment for domains where less prior knowledge is accessible is
a relatively novel application of pervasive computing. Here augmentation of physical training devices with sensors has been
used as the basis for monitoring outdoor sports such as skiing [11] or tennis [12], as well as indoors, such as recognition
and tracking of free-weight exercises with accelerometers in a glove [13]. In the gym, sensor data from balance board
training [14,15] has been used to provide feedback on the performance quality. Furthermore, body-worn inertial sensors
have been used for the assessment of (professional) athletes in sports such as snow-boarding [16], swimming [17] and