Static optimization is commonly employed in musculoskeletal modeling to estimate muscle and joint loading; however, the ability of this approach to predict shoulder muscle stabilizing function is poorly understood. This includes the roles of the rotator cuff muscles which, as antagonist muscles, contribute negatively to a net joint moment and are known to be important for maintaining glenohumeral joint compression. This study aimed to develop a neuromusculoskeletal model driven entirely from electromyography (EMG) data recorded from the major superficial and deep shoulder muscles, and to compare shoulder muscle and joint force predictions from the EMG-driven model with those calculated using static optimization. Four healthy adults performed six sub-maximal upper-limb contractions including shoulder abduction, adduction, flexion, extension, internal rotation and external rotation. EMG data were simultaneously measured from 16 shoulder muscles using surface and intramuscular electrodes, and joint motion evaluated using video motion analysis. Muscle and joint forces were calculated using both a calibrated EMG-driven neuromusculoskeletal modeling framework, and model simulations that employed static optimization. The EMGdriven model predicted antagonistic muscle function for pectoralis major, latissimus dorsi and teres major during abduction and flexion; supraspinatus during adduction; middle deltoid during extension; and subscapularis, pectoralis major and latissimus dorsi during external rotation. In contrast, static optimization neural solutions showed little or no recruitment of these muscles, and preferentially activated agonistic prime movers with large moment arms.Glenohumeral joint force calculations consequently varied between models, for instance, during internal rotation (mean difference: 41.1%BW). The findings suggest that static optimization may under-estimate activity of shoulder muscle antagonists, and therefore, their contribution to glenohumeral joint stability.

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The implementation of the Shari'a and the institutionalization of gender inequality in the aftermath of the revolution led to the disillusionment of the gender-sensitive Islamist women and triggered their discontent. Through their involvement in politics they attempted to present a different reading of Islam and Islamic laws which would be more attentive to the condition of women. These endeavours failed, however, because on the one hand they were still largely based on traditionalist interpretations, and on the other hand, the condition of women did not constitute a priority for the political and religious elite during the Iraq-Iran War . The end of the war and the implementation of 'Reconstruction Policies' provided an opportunity for a new generation of gender-conscious Islamist women to seek allies among secular women, to present a modern reading of Islam, and make radical demands for change in women's status by using politics as a potent agent. This article, which is largely based on personal interviews with some of these vocal women, traces their aspirations and endeavours, their identity formation, and the outcomes of their mobilization.

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Iran's government has tended to enforce gender social relations through both family and employment policies. Officially, women's employment is discouraged unless it is necessary for her family's survival, and the home is considered the best and the most suitable place for women. The state's discourse makes a sharp distinction between public and private spheres. Nonetheless, women's higher literacy rates and the increasing number of college educated women combined with high inflation, which has lowered both the purchasing power of middle and lower class households, and women's aspirations for financial independence and intellectual autonomy, have led them to seek paid employment. The most educated women target public administration or the private sector, while less educated women seek job opportunities in the informal sector of the economy. Decisionmaking authority within the family and the quest for gender equality in Iranian society are two of the outcomes of women's paid employment that is likely to alter gendered power relations.

Powered ankle exoskeletons (PAEs) are robotic devices developed for gait assistance, rehabilitation, and augmentation. To fulfil their purposes, PAEs vastly rely heavily on their sensor systems. Human–machine interface sensors collect the biomechanical signals from the human user to inform the higher level of the control hierarchy about the user’s locomotion intention and requirement, whereas machine–machine interface sensors monitor the output of the actuation unit to ensure precise tracking of the high-level control commands via the low-level control scheme. The current article aims to provide a comprehensive review of how wearable sensor technology has contributed to the actuation and control of the PAEs developed over the past two decades. The control schemes and actuation principles employed in the reviewed PAEs, as well as their interaction with the integrated sensor systems, are investigated in this review. Further, the role of wearable sensors in overcoming the main challenges in developing fully autonomous portable PAEs is discussed. Finally, a brief discussion on how the recent technology advancements in wearable sensors, including environment—machine interface sensors, could promote the future generation of fully autonomous portable PAEs is provided.

Walking independently is essential to maintaining our quality of life but safe locomotion depends on perceiving hazards in the everyday environment. To address this problem, there is an increasing focus on developing assistive technologies that can alert the user to the risk destabilizing foot contact with either the ground or obstacles, leading to a fall. Shoe-mounted sensor systems designed to monitor foot-obstacle interaction are being employed to identify tripping risk and provide corrective feedback. Advances in smart wearable technologies, integrating motion sensors with machine learning algorithms, has led to developments in shoe-mounted obstacle detection. The focus of this review is gait-assisting wearable sensors and hazard detection for pedestrians. This literature represents a research front that is critically important in paving the way towards practical, low-cost, wearable devices that can make walking safer and reduce the increasing financial and human costs of fall injuries.

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