
Key Findings
Point-of-care testing (POCT) has emerged as a transformative approach in modern healthcare for the rapid detection of physiological abnormalities through minimally or non-invasively collected samples. Biological matrices such as saliva, urine, hair, blood, and interstitial fluid contain clinically significant biomarkers that may serve as indicators of physiological disorders. Among these, cortisol is the key stress biomarker and exerts substantial effects on body metabolism, acting on both peripheral tissues and the CNS. This review comprehensively outlines the evolution of cortisol detection strategies, progressing from conventional laboratory-based immunoassays to advanced analytical platforms, including electrochemical biosensors, wearable devices, and microfluidic systems. Accurate and reliable detection of elevated cortisol levels is crucial for improving diagnostic, therapeutic, and preventive strategies for stress-related disorders. By tracing the analytical window, the work describes the detection of cortisol from traditional immunoassays to innovative biosensing platforms. Moreover, recent advances in nanomaterials, sensor design, and data integration have enabled continuous, on-site monitoring of cortisol levels, thereby enhancing their applicability across diverse clinical and non-clinical settings. This integration of physiological insight with technological advancement provides a comprehensive overview of developments in cortisol assessment, connecting fundamental endocrine science with practical diagnostic applications. The review underscores the potential of next-generation POCT systems to improve early diagnosis, therapeutic monitoring, and personalized healthcare through real-time biomarker analysis.
Why This Matters for Body-Mind Practice
[Draft — editorial context needed]
Source
- Cortisol as a stress biomarker: analytical perspectives and challenges. — Clinica chimica acta; international journal of clinical chemistry
- Clinica chimica acta; international journal of clinical chemistryRead Source →


