The principal aim of the present study was to examine the validity of the Computer Science and Applications (CSA) activity monitor during level walking in coronary artery disease (CAD) patients. As a secondary aim, we evaluated the usefulness of two previously published energy expenditure (EE) prediction equations. Thirty-four subjects (29 men and five women), all with diagnosed CAD, volunteered to participate. Oxygen uptake (VO2) was measured by indirect calorimetry during walking on a motorized treadmill at three different speeds (3.2, 4.8 and 6.4 km h-1). Physical activity was measured simultaneously using the CSA activity monitor, secured directly to the skin on the lower back (i.e. lumbar vertebrae 4-5) with an elastic belt. The mean (+/- SD) activity counts were 1208 +/- 429, 3258 +/- 753 and 5351 +/- 876 counts min-1, at the three speeds, respectively (P < 0.001). Activity counts were significantly correlated to speed (r = 0.92; P < 0.001), VO2 (ml kg-1 min-1; r = 0.87; P < 0.001) and EE (kcal min-1; r = 0.85, P < 0.001). A stepwise linear regression analysis showed that activity counts and body weight together explained 75% of the variation in EE. Predicted EE from previously published equations differed significantly when used in this group of CAD patients. In conclusion, the CSA activity monitor is a valid instrument for assessing the intensity of physical activity during treadmill walking in CAD patients. Energy expenditure can be predicted from body weight and activity counts.