Wearable ultrasound sensing systems are rapidly emerging for precise, continuous, and intuitive biomedical monitoring and human-in-the-loop interaction in healthcare, industry, and rehabilitation. These systems must operate under stringent constraints on size, weight, and power while delivering actionable physiological and functional information. Advances in micromachined transducers, conformable electronics, low-power signal processing, and edge artificial intelligence (AI) have enabled the first generation of wearable prototypes, yet integration of hardware and software at the system-level remains a major barrier to mass deployment. This review maps the technology readiness and architectures of wearable ultrasound systems, and examines critical design trade-offs, including edge versus cloud-based processing and pulse-echo versus coded signal approaches. We identify recurring design principles and argue that modular, scalable, and reusable platforms are key to lowering development barriers and accelerating translation from prototypes to commercial deployment across healthcare, industrial, and consumer domains.
Weik et al. (Thu,) studied this question.