Coaching technology, wearables and exergames can provide quantitative
feedback based on measured activity, but there is little evidence of
qualitative feedback to aid technique improvement. To achieve personalised
qualitative feedback, we demonstrated a proof-of-concept prototype combining
kinesiology and computational intelligence that could help improving tennis
swing technique utilising three-dimensional tennis motion data acquired from
multi-camera video. Expert data labelling relied on virtual 3D stick figure
replay. Diverse assessment criteria for novice to intermediate skill levels and
configurable coaching scenarios matched with a variety of tennis swings (22
backhands and 21 forehands), included good technique and common errors. A set
of selected coaching rules was transferred to adaptive assessment modules able
to learn from data, evolve their internal structures and produce autonomous
personalised feedback including verbal cues over virtual camera 3D replay and
an end-of-session progress report. The prototype demonstrated autonomous
assessment on future data based on learning from prior examples, aligned with
skill level, flexible coaching scenarios and coaching rules. The generated
intuitive diagnostic feedback consisted of elements of safety and performance
for tennis swing technique, where each swing sample was compared with the
expert. For safety aspects of the relative swing width, the prototype showed
improved assessment ...Comment: TB
