Animals (Basel). 2025 May 22;15(11):1517. doi: 10.3390/ani15111517.

ABSTRACT

Myofascial pain syndrome (MPS) is a common source of musculoskeletal pain, characterized by trigger points (TrPs). In horses, MPS is frequently underdiagnosed, and evidence on DN effectiveness is limited. This study investigated whether DN can improve the biomechanics in horses using an artificial intelligence (AI)-based markerless smartphone application (app). Fourteen horses participated, including nine used in assisted therapy, four leisure horses, and one with mixed use. The presence of TrPs was evaluated in six muscles through manual palpation: brachiocephalicus, trapezius, gluteus medius, biceps femoris, semitendinosus, and quadriceps femoris. The horses were divided into a treatment group (TG) (n = 7) and control group (CG) (n = 7). Biomechanical data were recorded in a straight line at a trot before the treatment (T0), immediately after the treatment (T1), and 72 h post-treatment (T72). The stride frequency (SF) was significantly lower (p < 0.05) at 72 h compared with both before and immediately after the treatment. The SF of the TG at 72 h was significantly lower than the SF of the CG at T1 (p < 0.05). Non-significant differences were observed for both the asymmetry push-off and impact phase variables, except for the forelimb head range of motion (FHROM) severity, which was significantly (p < 0.05) greater in the CG than in the TG. This study suggests that DN may enhance the gait quality in horses with MPS.

PMID:40508982 | DOI:10.3390/ani15111517