Exosomes are cell-secreted nanoscale vesicles 30-150 nm in size and encompass a diverse array of biomolecules, including lipids, proteins, and nucleic acids. Exosomes play pivotal roles during the intercellular exchange of materials and information, and are closely associated with the onset and progression of a variety of diseases. Therefore, comprehensively investigating exosomes is very important in terms of disease diagnosis and treatment. However, exosomes are genetically heterogeneous and are composed of different materials. Additionally, exosome-size and packing-specific-biomarker heterogeneities result in biofunction diversity. Moreover, isolating and analyzing exosomes is highly challenging owing to their small sizes and heterogeneities. Accordingly, effective separation methods and analytical techniques for highly specifically and efficiently identifying exosomes are urgently needed in order to better understand their functionalities. While separation and analysis is required to reveal exosome heterogeneity, the former is confronted by three primary challenges. Firstly, exosome heterogeneity (including heterogeneous marker expressions and size heterogeneity that results in heterogeneous functions) results in systems that are very difficult to separate. Secondly, the coexistence of non-vesicular contaminants (lipoprotein nanoparticles, soluble proteins, nucleic acids, etc.) and the complex matrix effects of body fluids also contribute to separation difficulties. Thirdly, enrichment is a highly challenging task owing to low exosome concentrations. Traditional methods, such as ultracentrifugation and size-exclusion chromatography, fall short in terms of their abilities to precisely separate and analyze exosomes. On the other hand, microfluidics has emerged as a robust tool for the efficient analysis of complex biological samples and is characterized by miniaturization, precise control, high throughput, automation, and integration. Firstly, the operability, integrability, and modifiability of a microfluidics system facilitate exosome separation and purification based on surface properties, size, charge, and polarity. Secondly, the use of a microfluidics approach, with its high throughput, low reagent consumption, and multichannel manipulability, greatly facilitates preparing exosomes and enhancing their concentrations. Thirdly, microfluidics ensures that diverse separation methods are compatible with downstream analysis techniques. Exosomes are highly heterogeneous; hence, they are classified by type and subpopulation (according to origin, size, molecular markers, functions, etc.). This paper first discusses microfluidics techniques for separating exosomes and examines various separation strategies grounded in the physicochemical properties of exosomes. We then analyze exosome detection methodologies that use microfluidics platforms and encompass traditional group-exosome analysis techniques and novel single-exosome analysis approaches. Finally, we discuss future clinical applications of microfluidics technology in exosome research, particularly its potential for diagnosing and treating diseases, thereby underscoring the applications value of microfluidics technology in the realm of personalized and precision medicine. Furthermore, cutting-edge microfluidics platforms offer novel perspectives for purifying and preparing EVs owing to precise fluid control, integration, miniaturization, and high-throughput characterization. EV populations, subpopulations, and single vesicles can be purified based on their physicochemical properties and microfluidics features. Comprehensive lab-on-a-chip methods are promising in terms of separating EVs based on traits, such as size, surface markers, and charge, and for obtaining highly pure EVs. Recycled EV samples can be prepared by controlling the high-throughput and multichannel capabilities of microfluidics approaches. The transition from bulk EV analysis to single-vesicle analysis provides opportunities to explore the heterogeneous nature of EVs, thereby augmenting their potential for disease diagnosis.