发表机构
Vanderbilt University; Milton Academy（范德堡大学; 米尔顿学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
SPAR是一种基于八IMU服装和压力鞋垫的拳击可穿戴分析系统，通过分类出拳为专家或新手，并在三个层级提供可解释反馈，在17名参与者、4,713次出拳中达到0.842的AUC。
AI 中文摘要
出拳是一种弹道式、全身性的动作，由从腿部经躯干到手臂的动力链驱动，其中微小的顺序错误便会将得分击打与失误区分开来。可穿戴传感器可以在健身房中捕捉这一动作，但大多数可部署系统仅能分类出拳类型，而非评估出拳质量。我们提出了技能画像与可归因推理（SPAR）系统，该系统由八惯性测量单元（IMU）服装和压力鞋垫组成，将每次出拳分类为专家或新手，并将对该预测的解释视为反馈。反馈只有在接收者能够据此采取行动时才有用，因此SPAR在三个层级上解释预测：为分析师提供逐关节归因，为教练提供动力链层级的反事实分析，以及为运动员提供这两者的通俗语言叙述。在17名参与者和4,713次出拳中，SPAR达到了留一参与者交叉验证的AUC为0.842（参与者间95%置信区间[0.769, 0.907]）。一个冻结的时间序列基础模型编码关节角度和足底力序列，一个在该队列上训练的小型变换器对编码进行分类。我们审计了两个定量层级，并报告了对六名执业拳击教练访谈的主题分析得出的六个主题。
英文摘要
A punch is a ballistic, full-body action driven by a kinetic chain running from the legs through the trunk to the arm, where a small sequencing error separates a scoring strike from a miss. Wearable sensors can capture this movement in the gym, but most deployable systems only classify which punch was thrown rather than assess how well it was thrown. We present Skill Profiling with Attributable Reasoning (SPAR), an eight-IMU garment and pressure-insole system that classifies each punch as expert or novice and treats an explanation of that prediction as feedback. Feedback is only useful if the person receiving it can act on it, so SPAR explains the prediction at three tiers, a per-joint attribution for the analyst, a counterfactual over kinetic-chain layers for the coach, and a plain-language narrative of the two for the athlete. Across 17 participants and 4,713 punches, SPAR reaches a leave-one-participant-out AUC of 0.842 (95% CI [0.769, 0.907] over participants). A frozen time-series foundation model encodes the joint-angle and plantar-force series, and a small transformer trained on the cohort classifies the encoding. We audit the two quantitative tiers and report six themes from a thematic analysis of interviews with six practicing boxing coaches.
