Advancements in Tactile Biosensors: The Role of Additive Manufacturing and Machine Learning in Biomedical Applications

Tactile biosensors areimportant for biomedical applications that require sensing mechanical stimuli like pressure, strain, and vibration. This review considers developments in tactile biosensor designs through additive manufacturing (AM) and machine learning (ML). The review defines four sensor mechanisms, piezoelectric, piezoresistive, strain gauge, and capacitive, and summarizes their working principles, materials, and biomedical relevance. Various additive manufacturing methods, such as direct ink writing, fused deposition modeling, stereolithography, and selective laser sintering, are discussed for their properties that provide customization, multimaterial, and sensor sensitivity improvements. Signal‐acquisition and processing strategies are also reviewed, as well as ML algorithms for classification and design optimization. Finally, this review paper indicates current obstacles for commercialization, for example, limitations of materials, variability of performance, or lack of scaling up for manufacturing. Tactile biosensor applications in biomedical engineering will continue to merge materials science, AM, and, in some contexts, data‐driven methods to provide the next evolution of biosensors that will offer reliable, accessible, and functional biosensors.