Friction caused at different articular surfaces in horses’ joints can produce various vibration signals. In this study, we collected and analyzed the articular vibration signals in the fetlock joints of a healthy horse, an aged horse, and a horse with laminitis using the equine vibration arthrometry system (EVAS). The data obtained from the EVAS enabled the researchers to easily understand the condition of the horses’ inner joints and to differentiate between the joints of healthy limbs and those of diseased limbs with musculoskeletal disorders. Furthermore, we also developed mathematical algorithms to analyze the data from the EVAS in this study. We identified two periodic waveform cycles for each horse’s step in the time domain. The negative waveform cycle first appeared at each aged horse’s step. The root-mean-square (RMS) values of both the positive and negative waveform cycles were significantly larger at the first periodic waveform in the aged horse. In contrast, the positive waveform cycle first appeared in each healthy horse’s step and the RMS values of the positive waveform cycle were significantly larger in the healthy horse. We also measured the energy of the articular vibration signals of the healthy and aged horses in the first and second periodic waveform cycle during each horse’s step. By analyzing and comparing articular vibration signals in these horses, we were able to determine which of the horses had a musculoskeletal disorder. EVAS is a simple, convenient and non-invasive method of identifying articular problems in equine joints.