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The ambulatory monitoring of human movement can provide valuable information regarding the degree of functional ability and general level of activity of individuals. Since walking is a basic everyday movement, automatic step detection or step counting is very important in developing ambulatory monitoring systems. This paper is concerned with the development and the preliminary validation of a step counter (SC) designed to operate also in conditions of slow and intermittent ambulation. The SC was based on processing the accelerometer data measured by a Gear 2 smartwatch running a custom wearable app, named ADAM. A data set of eight users, for a total of 80 trials, was used to tune ADAM. Finally, ADAM was compared with two different commercial SCs: the native SC running on the Gear 2 smart watch and a waist-worn SC, the Geonaute ONSTEP 400. A second data set of eight additional users for a total of 80 trials was used for the assessment study. The three SCs performed quite similarly in conditions of normal walking over long paths (1%-3% of mean absolute relative error); ADAM outperformed the two other SCs in conditions of slow and intermittent ambulation; the error incurred by ADAM was limited to 5%, which is significantly lower than errors of 20%-30% incurred by the two other SCs.