Wireless measurement of resistance variation is particularly desirable inside confined cavities where wire connection and battery replacement are undesirable. Compared to capacitive or inductive transducers, resistive transducers have better availability, whose resistance changes can be directly converted into detectable voltages by electric bridges. However, to wirelessly operate electric bridges on batteryless platforms, multistage circuits are required to convert dc signals into wireless signals, making the whole system hard to miniaturize without using complicated integrated circuits. Alternatively, resistive transducers can be incorporated into passive
resonators for contactless characterization by the backscattering method. This design, however, is ineffective beyond the near field, and it requires complicated line shape analysis of resonators’ frequency response curves. Here, we will significantly improve the remote detectability of a resistive transducer, by inductively coupling it with a parametric resonator. Upon activation by wireless pumping power with an external antenna, the parametric resonator can self-oscillate and emit strong oscillation signals. The temperature-induced resistance change is converted into linear frequency shifts of the oscillation signal that can be detected over large distance separations for up to 20-fold the sensor’s own dimension. Every 0.1 °C of temperature change can be converted into 8 kHz of frequency shift that is approximately threefold larger than the linewidth of oscillation peak. This sensor maintains good linearity between 25 °C and 41 °C, providing enough range for physiological monitoring. In conclusion, we have fabricated a resistance-to-frequency converter for remote detection of resistance changes via a wirelessly powered parametric oscillator. Besides this proof-of-concept demonstration for temperature sensing, the general concept of resistance-to-frequency conversion will improve the remote detectability of a broad range of resistive transducers for physiological and environmental monitoring.