a b s t r a c tAssessment of spinal stiffness is widely used by manual therapy practitioners as a part of clinical diagnosis and treatment selection. Although studies have commonly found poor reliability of such procedures, conflicting evidence suggests that assessment of spinal stiffness may help predict response to specific treatments. The current study evaluated the criterion validity of manual assessments of spinal stiffness by comparing them to indentation measurements in patients with low back pain (LBP). As part of a standard examination, an experienced clinician assessed passive accessory spinal stiffness of the L3 vertebrae using posterior to anterior (PA) force on the spinous process of L3 in 50 subjects (54% female, mean (SD) age ¼ 33.0 (12.8) years, BMI ¼ 27.0 (6.0) kg/m 2 ) with LBP. A criterion measure of spinal stiffness was performed using mechanized indentation by a blinded second examiner. Results indicated that manual assessments were uncorrelated to criterion measures of stiffness (spearman rho ¼ 0.06, p ¼ 0.67). Similarly, sensitivity and specificity estimates of judgments of hypomobility were low (0.20 e0.45) and likelihood ratios were generally not statistically significant. Sensitivity and specificity of judgments of hypermobility were not calculated due to limited prevalence. Additional analysis found that BMI explained 32% of the variance in the criterion measure of stiffness, yet failed to improve the relationship between assessments. Additional studies should investigate whether manual assessment of stiffness relates to other clinical and biomechanical constructs, such as symptom reproduction, angular rotation, quality of motion, or end feel.Published by Elsevier Ltd.

Smart cities contain intelligent things which can intelligently automatically and collaboratively enhance life quality, save people's lives, and act a sustainable resource ecosystem. To achieve these advanced collaborative technologies such as drones, robotics, artificial intelligence, and Internet of Things (IoT) are required to increase the smartness of smart cities by improving the connectivity, energy efficiency, and quality of services (QoS). Therefore, collaborative drones and IoT play a vital role in supporting a lot of smartcity applications such as those involved in communication, transportation, agriculture,safety and security, disaster mitigation, environmental protection, service delivery, energy saving, e-waste reduction, weather monitoring, healthcare, etc. This paper presents a survey of the potential techniques and applications of collaborative drones and IoT which have recently been proposed in order to increase the smartness of smart cities. It provides a comprehensive overview highlighting the recent and ongoing research on collaborative drone and IoT in improving the real-time application of smart cities. This survey is different from previous ones in term of breadth, scope, and focus. In particular, we focus on the new concept of collaborative drones and IoT for improving smart-city applications. This survey attempts to show how collaborative drones and IoT improve the smartness of smart cities based on data collection, privacy and security, public safety, disaster management, energy consumption and quality of life in smart cities. It mainly focuses on the measurement of the smartness of smart cities, i.e., environmental aspects, life quality, public safety, and disaster management.

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This paper studies the network performance of collaboration between the Internet of public safety things (IoPST) and drones. Drones play a vital role in delivering timely and essential wireless communication services for the recovery of services right after a disaster by increasing surge capacity for the purposes of public safety, exploring areas that are difficult to reach, and providing an area of rapid coverage and connectivity. To provide such critical facilities in the case of disasters and for the purposes of public safety, collaboration between drones and IoPST is able to support public safety requirements such as real-time analytics, real-time monitoring, and enhanced decision-making to help smart cities meet their public safety requirements. Therefore, the deployment of drone-based wireless communication can save people and ecosystems by helping public safety organizations face threats and manage crises in an efficient manner. The contribution of this work lies in improving the level of public safety in smart cities through collaborating between smart wearable devices and drone technology. Thus, the collaboration between drones and IoPST devices establishes a public safety network that shows satisfying results in terms of enhancing efficiency and information accuracy.

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