Human sweat, a complex biofluid, provides valuable insights across various scientific disciplines. Sweat metabolite analysis holds promise for enhancing screening, diagnosis, and self-monitoring of numerous conditions, enabling personalized medical interventions. The motivation for this article was to illustrate the unique advantage of sweat analysis including the opportunity for non-invasive and continuous collection with realtime monitoring and the ability to reflect dynamic metabolic changes that other modality such as DNA or saliva do not exhibit. This review provides a comprehensive overview of human sweat, covering its origins, physical characteristics, functional roles, factors influencing it's composition, different sensing devices, and methods for the analysis. By reviewing over 200 studies, essential factors affecting sweat analysis's validity, reliability, and reproducibility were verified. These included the anatomical site of sweat sampling, skin integrity, temperature, humidity, timing, metabolic quenching, transport, storage, and subjectspecific factors like diet, emotional state, and drug use. Sweat contains various metabolites that serve as biomarkers for health monitoring, such as glucose for type II diabetes, lactate for cardiopulmonary health, cortisol for measuring stress levels to prevent depression and anxiety, and electrolytes for maintaining fluid balance and detecting conditions like cystic fibrosis. The approaches to analyzing sweat can be categorized into chemical analysis techniques (LC-MS, GC-MS, MS/MS), spectroscopic methods (HSI, Raman Spectroscopy), biochemical assays, machine learning applications, forensic analysis, and health monitoring devices, each offering unique capabilities for identification and diagnostic purposes. However, advancements in identifying identifiable data from sweat raise substantial ethical and privacy concerns.