Dupuytren’s fasciectomy requires precise separation of diseased cords from adjacent neurovascular structures, yet conventional scalpels offer no intrinsic tissue selectivity and depend entirely on surgeon skill. This thesis presents Fascinex, a handheld oscillation-assisted cutting device built on a commercially available actuator (Dragonhawk X8) and equipped with custom blade geometries designed to exploit stiffness-dependent mechanical response for selective cutting. Multilayer anatomical phantoms were developed for evaluation, and clinicians compared Fascinex (6025 and 9000 RPM) with a scalpel in skin-incision and nerve-extraction tasks. While the scalpel remained superior in cutting speed and edge smoothness, Fascinex exhibited characteristic mechanical selectivity: stiff cord-like structures were incised reliably, whereas softer tissues deformed and remained preserved. At 9000 RPM, cutting deviations approached those of the scalpel, with no damage to simulated nerves or vessels. These results demonstrate proof-of-concept feasibility for stiffness-based tissue discrimination under oscillatory loading and highlight directions for improving blade design, vibration control, and ergonomics.