Objective: The aim of this study was to validate a novel pictorial-based Longshi Scale for evaluating a patient’s disability by healthcare professionals and non-professionals. Design: Prospective study. Setting: Rehabilitation departments from a grade A, class 3 public hospital, a grade B, class 2 public hospital, and a private hospital and seven community rehabilitation centers. Subjects: A total of 618 patients and 251 patients with functional disabilities were recruited in a two-phase study, respectively. Main measures: Outcome measure: pictorial scale of activities of daily living (ADLs, Longshi Scale). Reference measure: Barthel Index. The Spearman correlation coefficient was used to analyze the validity of Longshi Scale against Barthel Index. Results: In phase 1 study, from March 2016 to August 2016, the results demonstrated that the Longshi Scale was both reliable and valid (intraclass correlation coefficient based on two-way random effect (ICC2,1) = 0.877–0.974 for intra-rater reliability; ICC2,1 = 0.928–0.979; κ = 0.679–1.000 for inter-rater reliability; intraclass correlation coefficient based on one-way random effect (ICC1,1) = 0.921–0.984 for test–retest reliability and Spearman correlation coefficient = 0.836–0.899). In the second phase, in March 2018, results further demonstrated that the Longshi Scale had good inter-rater and intra-rater reliability among healthcare professionals and non-professionals including therapists, interns, and personal care aids (ICC1,1 = 0.822–0.882 on Day 1; ICC1,1 = 0.842–0.899 on Day 7 for inter-rater reliability). In addition, the Longshi Scale decreased assessment time significantly, compared with the Barthel Index assessment ( P < 0.01). Conclusion: The Longshi Scale could potentially provide an efficient way for healthcare professionals and non-professionals who may have minimal training to assess the ADLs of functionally disabled patients.

Weight-bearing exercise is a well-accepted physiotherapy to prevent osteoporosis for stroke patients. But the immobility of stroke patients limits the types and intensity of conventional interventions. Recent advances in robot-assisted therapeutic device provide an innovative way which could potentially overcome the above-mentioned limitations. However, the effects of robot-assisted physiotherapy on osteoporosis prevention have not been fully understood. The purpose of the present study is to develop an innovative theoretical framework to investigate the effects of static robot-assisted walking exercise on bone health. Through conducting a series of studies using a robot, force insoles and CT-image-based computational modeling, our results show that robot-assisted walking can significantly reduce the osteoporosis risk for stroke patients. However, the vertical peak ground reaction forces generated from static robot walking is generally lower than that from treadmill walking due to the fact that there are no heel strike and push-off effects in static robotic walking.