Shamsul Akmar Ab AZIZ, et al.: New regression model for predicting hand-arm vibration (HAV) oped regression model, we can easily predict HAV exposure from steering wheels for HAV exposure monitoring. ( Moving vehicles produce noise and vibrations that cause discomfort to drivers and passengers. There are many sources of this noise and vibrations, such as the engine, wind, chassis, and road-tire interaction. Vibration causes excitation of the chassis structure, which is transmitted via mechanical vibrations into the driver's compartment, where it can be felt as vehicle interior vibrations in the seat, steering wheel, and/or body floor 1) . Hand-arm vibration (HAV) is the vibration received by hands that are in direct contact with the surfaces of vibrating parts, such as steering wheels, and hand tools that produce vibrations, such as hand drills, chain saws, and grinders. Exposure to vibration from a vehicle depends on several factors, such as the type and design of the vehicle, speed, and environmental conditions. There are some physical variables relevant to the effects of hand-transmitted vibration, such as magnitude, frequency, direction of vibration, duration of exposure, area of contact with vibration, contact force (grip and push forces), hand posture, and environment 2) . HAV has been recognized as a significant hazard for the health and safety of workers. HAV syndrome (HAVS) is a general term embracing various kinds of health issues, including vascular disorders generally known as "vibration-induced white finger" (VWF). It causes impaired blood circulation and blanching of affected fingers and parts of the hand, neurological and musculoskeletal damage leading to numb- ∞ increased when the vehicle speed and HAV exposure increased. Discussion: For model validation, predicted and measured noise exposures were compared, and high coefficient of correlation (R 2 ) values were obtained, indicating that good agreement was obtained between them. By using the devel-