综述可穿戴设备行为识别技术演进与未来方向
Past, Present, and Future of Sensor-Based Human Activity Recognition Using Wearables: A Surveying Tutorial on a Still Challenging Task
- 梳理从手工特征到基础模型的演化路径
- 指出当前主流基准性能提升停滞
- 提供面向实际应用的实践教程
自可穿戴传感器人体活动识别（HAR）问世以来，已涌现出大量方法并被评估其识别能力。尽管从手工设计启发式特征时代至今取得了显著进展，但在多个主流基准上性能提升似乎已停滞，即便计算能力增强、传感器数据规模扩大且技术复杂度提高，仍未能达到“足够”的水平。如今，HAR领域正迎来新范式转变，开始引入基础模型中的世界知识。本文系统回顾了传感器驱动的HAR发展历程，涵盖其起源、当前状态及未来趋势，并附带一份实践教程，指导从业者构建面向真实应用场景的HAR系统。本综述为初学者和专家提供了一个全面的方法合集，旨在最终解决活动识别难题。
原文摘要 · Abstract (English)
In the many years since the inception of wearable sensor-based Human Activity Recognition (HAR), a wide variety of methods have been introduced and evaluated for their ability to recognize activities. Substantial gains have been made since the days of hand-crafting heuristics as features, yet, progress has seemingly stalled on many popular benchmarks, with performance falling short of what may be considered 'sufficient'-- despite the increase in computational power and scale of sensor data, as well as rising complexity in techniques being employed. The HAR community approaches a new paradigm shift, this time incorporating world knowledge from foundational models. In this paper, we take stock of sensor-based HAR -- surveying it from its beginnings to the current state of the field, and charting its future. This is accompanied by a hands-on tutorial, through which we guide practitioners in developing HAR systems for real-world application scenarios. We provide a compendium for novices and experts alike, of methods that aim at finally solving the activity recognition problem.
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