From Analysis to Engagement: AI-Supported Performance Feedback in Sport

PhD Qualifying Examination


Title: "From Analysis to Engagement: AI-Supported Performance Feedback in Sport"

by

Miss Qiaoyi CHEN


Abstract:

Artificial intelligence has significantly advanced sports performance 
analysis, enabling detailed assessments of technique, training load, and 
tactical decision-making from video, wearable sensors, and positional data. 
However, translating these analytical insights into improved athletic 
outcomes depends critically on how athletes and coaches engage with and 
reflect on AI-generated feedback: a challenge that sports science and HCI 
have pursued with differing methods and evaluation criteria, and limited 
cross- disciplinary integration.

To bridge this gap, we present a systematic survey of AI-driven sports 
coaching systems through a two-stage analytical framework: Stage 1 examines 
how AI systems extract usable performance insights; Stage 2 examines how 
athletes and coaches engage with and interpret those insights to support 
behaviour change. Following PRISMA guidelines, we searched major HCI and 
sports science publication venues, identifying 30 papers organised by 
analysis targets and reflection settings.

Our analysis reveals three structural gaps in existing systems: limited 
support for longitudinal tracking of athlete development; limited integration 
between coach-side analysis and athlete-facing feedback; and limited 
consideration of both the athlete's capability profile and the demands of 
specific tasks. In addition, we observe a gap in population coverage: 
para-athletes, youth athletes, and recreational participants in emerging 
sports remain largely underrepresented, and the reference models underlying 
current AI systems are primarily built from data that excludes them.

We further discuss how emerging AI capabilities (particularly large language 
models, multimodal foundation models, and physiological sensing) create 
concrete opportunities to address these gaps, reframing AI sports coaching 
from a pipeline of analyses into an adaptive, longitudinal, and socially 
situated coaching support system.


Date:                   Thursday, 2 April 2026

Time:                   9:00am - 11:00am

Venue:                  Room 2132C
                        Lift 22

Committee Members:      Dr. Xiaojuan Ma (Supervisor)
                        Dr. Arpit Narechania (Chairperson)
                        Prof. Raymond Wong