No abstract

No abstract

Joint accessory motion testing (JAMT) is a standard procedure used by manual therapists to assess and treat musculoskeletal disorders. Joint accessory motion (JAM) is movement that occurs between joint surfaces, and can be induced by applying force. The motion amount, end feel, symptoms, and resistance perceived by therapists during test procedures are recorded as evidence for the diagnosis, prognosis, treatment decision making, and intervention outcome. However, previous studies have shown that accessory motion tests have insufficient reliability. Recently, many instruments have been developed to increase test reliability, but these instruments quantify the test results with a single probe and utilize the external environment as a reference. Therefore, the measured displacement amount may be affected by other spinal segments. This study proposes an objective portable measurement device with two indenter probes for spinal JAMT, wherein the JAM was quantified by displacement and force measurements between two bones. The instrument was verified with a homemade spinal simulator and computer simulation. The results showed that the force-displacement curves measured by the JAMT device (JAMTD) and those simulated by the computer model exhibited similar characteristics. Moreover, a two-probe measurement could distinguish the differences in stiffness better than a one-probe measurement.

Considering the trend of aging societies, accompanying technology can help frail, elderly individuals participate in daily activities. The ideal accompanying robot should accompany the user in a proper position according to the activity scenarios and context; the prerequisite is that the accompanying robot should quickly move to a designated position and closely maintain it regardless of the direction in which the user moves. This paper proposes a user local coordinate-based strategy to satisfy this need. As a proof of concept, a novel “string-pot” approach was utilized to measure the position difference between the robot and the target. We implemented the control strategy and assessed its performance in our gait lab. The results showed that the robot can follow the user in the designated position while the user performs forward, backward, and lateral movements, turning, and walking along a curve.