Parkinson’s disease (PD) is the second most common neurodegenerative disorder, chronically and progressively impairing patients’motor functions and significantly reducing their quality of life. At present, the accurate early diagnosis of PD faces challenges, and there is a lack of biomarkers for monitoring disease progression and assessing treatment efficacy. Collecting and analyzing kinematic and dynamic indicators of patients’handwriting, such as size, speed, acceleration, fluency, and pressure, can help in the early recognition of PD, timely monitoring of disease progression, and assessment of treatment efficacy. With the continuous development of handwriting analysis technology and deepening research, this method is expected to become an important adjunct tool in the diagnosis, treatment, and follow-up of PD.