A Holter monitor is an ambulatory device for continuous and long-term electrocardiography (ECG) monitoring for various clinical purposes. Information on a patient's physical activity improves the clinical interpretation of ECG data. In this study, we propose a static posture and dynamic activity classification algorithm with a Holter-mounted accelerometer. This algorithm separates an acceleration signal into static gravity and dynamic activity acceleration. The static gravity is used to calculate a tilt angle, which discriminates static posture intuitively. The dynamic acceleration is also used to classify dynamic activity. The proposed algorithm was implemented and tested in a Holter monitor. Its functional feasibility was shown for six healthy subjects. The Holter monitor was attached to the chest, front beltline, and lateral beltline alternatively.