Background: While over half of stroke survivors recover the ability to walk without assistance, deficits persist in the performance of walking adaptations necessary for safe home and community mobility. One such adaptation is the ability to walk or step backward. Post-stroke rehabilitation rarely includes backward walking (BW) assessment and BW deficits have not been quantified in post-stroke community ambulators.
Objective: To quantify spatiotemporal and kinematic BW characteristics in post-stroke community ambulators and compare their performance to controls.
Methods: Individuals post-stroke (n = 15, 60.1 ± 12.9 years, forward speed: 1.13 ± 0.23 m/s) and healthy adults (n = 12, 61.2 ± 16.2 years, forward speed: 1.40 ± 0.13 m/s) performed forward walking (FW) and BW during a single session. Step characteristics and peak lower extremity joint angles were extracted using 3D motion analysis and analyzed with mixed-method ANOVAs (group, walking condition).
Results: The stroke group demonstrated greater reductions in speed, step length and cadence and a greater increase in double-support time during BW compared to FW (p < .01). Compared to FW, the post-stroke group demonstrated greater reductions in hip extension and knee flexion during BW (p < .05). The control group demonstrated decreased plantarflexion and increased dorsiflexion during BW, but these increases were attenuated in the post-stroke group (p < .05).
Conclusions: Assessment of BW can unmask post-stroke walking impairments not detected during typical FW. BW impairments may contribute to the mobility difficulties reported by adults post-stroke. Therefore, BW should be assessed when determining readiness for home and community ambulation. 相似文献
Our objective was to develop and evaluate 3 semiautomatic computer-aided diagnostic (CAD) schemes for distinguishing between benign and malignant pulmonary nodules by use of features extracted from CT, 18F-FDG PET, and both CT and 18F-FDG PET. METHODS: We retrospectively collected 92 consecutive cases of pulmonary nodules (<3 cm) in patients who underwent both thoracic CT and whole-body PET/CT. Forty-two of the nodules were malignant and 50 benign, as confirmed by pathologic examination and clinical follow-up. The interval between CT and PET was less than 1 mo. Four clinical parameters, including patient age, sex, smoking status, and history of previous malignancy, were used for the CAD schemes. Sixteen CT features based on size, shape, margin, and internal structure of nodules were independently rated subjectively by 2 chest radiologists. Four PET features were viewed on a PET/CT workstation. CAD schemes based on clinical parameters together with CT features, PET features, and both CT and PET features were then used to differentiate benign from malignant nodules. Finally, the output from the CAD schemes was evaluated by use of receiver-operating-characteristic analysis. RESULTS: When we used clinical parameters and CT features as input units (CAD scheme 1), the area under the receiver-operating-characteristic curve (A(z) value) of the CAD scheme was 0.83. When we used clinical parameters and PET features as input units (CAD scheme 2), the A(z) value for the computer output was 0.91. However, when we used all data as input units (CAD scheme 3), the A(z) value for the computer output was 0.95. The performance of CAD scheme 3 was better than that of CAD scheme 1 or 2. A statistically significant difference existed between the A(z) values of CAD schemes 3 and 2 (P = 0.037) and between those of CAD schemes 3 and 1 (P = 0.015). CONCLUSION: Our CAD scheme based on both PET and CT was better able to differentiate benign from malignant pulmonary nodules than were the CAD schemes based on PET alone and CT alone. 相似文献