The integration of soft and multifunctional materials in emerging technologies is becoming more widespread due to their ability to enhance or improve functionality in ways not possible using typical rigid alternatives. This trend is evident in various fields. For example, wearable technologies are increasingly designed using soft materials to improve modulus compatibility with biological systems and employing conformable interfaces for electrodes for enhanced signal integrity and user comfort. Likewise, surgical tools are leveraging soft material systems to reduce the risk of tissue damage through their inherent compliance. Soft material systems are also being incorporated into robots to improve safety in human-robot interactions, as in co-working and assistive applications.

However, the same lack of rigidity and complex constitutive behavior that make these material systems useful in emerging applications also present challenges in fully exploiting their capabilities. Soft substrates are continuously deformable and, without rigid constraints or simplifying operational assumptions, state inference can be difficult or impossible. In systems that exploit dynamic material properties, such as those using shape-memory alloys for actuation or thermoplastic polymers for stiffness tuning, system behavior is challenging to model from a controls perspective due to internal states that are difficult or impossible to measure in real time.

Exploiting these materials effectively requires improved sensor integration and device co-design. Here I discuss how sensing can be integrated to harness the inherent functionality of these non-traditional materials while preserving their novel properties and minimizing unnecessary design complexity. I first examine integration into existing systems, highlighting both the potential benefits and challenges of approaching sensorization in this way. Then I propose a more holistic design approach that embraces a synergistic relationship between material systems and their embedded sensors.