This article presents a fully integrated frequency-domain (FD) functional near-infrared spectroscopy (fNIRS) detection integrated circuit (IC) designed for non-invasive measurement of tissue metabolite optical properties. Departing from traditional static architectures, a dynamic light sensing architecture is proposed, which allows for the decoupling of time-of-flight (ToF) resolution from the system power consumption through duty-cycle modulation, thereby enhancing energy efficiency. In addition, to improve the measurement precision of both ToF and intensity loss, an inter-stabilized intensity and phase-to-digital converter (IS-IPDC) is proposed to resolve coupling issues between intensity and phase quantification. The chip is implemented in a standard 180-nm CMOS process. Test results indicate that the light ToF resolution is 2.2 ps within a 10-Hz bandwidth, while consuming only 12.5 mW. Thanks to its high resolution and crosstalk-free characteristics, compared with the high-precision instrument-based reference system, the maximum measurement errors for the absorption coefficient (mu(a)) and reduced scattering coefficient (mu(')(s)) are 4.2% and 4%, respectively. Finally, comprehensive in vitro and in vivo demonstrations demonstrate the IC's capabilities for metabolic imaging and long-term monitoring.

The non-invasive quantification of metabolite concentration is of significant importance in the fields of medical diagnosis and monitoring. Functional near-infrared spectroscopy (NIRS) offers a promising optical solution for this purpose. However, conventional continuous-wave (CW) NIRS systems only record light intensity, limiting analysis of optical absorption (μ a ) and reduced scattering (μ s ’) coefficient fluctuations in substances [1–2]. This hinders obtaining absolute metabolite concentrations, limiting the technology’s utility. Frequency-domain (FD) NIRS emits intensity-modulated light into human tissues, allowing simultaneous measurement of changes in optical intensity loss and light time-of-flight (ToF). It then determines absolute metabolite concentrations,.addressing key needs in brain functional imaging, drug metabolism studies and cancer diagnosis.