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Modern medical devices connected to public and private networks require additional layers of communication and management to effectively and securely treat remote patients. Wearable medical devices, for example, can detect position, movement, and vital signs; such data help improve the quality of care for patients, even when they are not close to a medical doctor or caregiver. In healthcare environments, these devices are called Medical Internet-of-Things (MIoT), which have security as a critical requirement. To protect users, traditional risk assessment (RA) methods can be periodically carried out to identify potential security risks. However, such methods are not suitable to manage sophisticated cyber-attacks happening in near real-time. That is the reason why dynamic RA (DRA) approaches are emerging to tackle the inherent risks to patients employing MIoT as wearable devices. This paper presents a systematic literature review of RA in MIoT that analyses the current trends and existing approaches in this field. From our review, we first observe the significant ways to mitigate the impact of unauthorised intrusions and protect end-users from the leakage of personal data and ensure uninterrupted device usage. Second, we identify the important research directions for DRA that must address the challenges posed by dynamic infrastructures and uncertain attack surfaces in order to better protect users and thwart cyber-attacks before they harm personal (e.g., patients’ home) and institutional (e.g., hospital or health clinic) networks.

The Industry 4.0 paradigm, since its initial conception in Germany in 2011, has extended its scope and adoption to a broader set of technologies. It is being considered as the most vital mechanism in the production systems lifecycle. It is the key element in the digital transformation of manufacturing industry all over the world. This scenario imposes a set of major unprecedented challenges which require to be overcome. In order to enable integration in horizontal, vertical, and end-to-end formats, one of the most critical aspects of this digital transformation process consists of effectively coupling digital integrated service/products business models with additive manufacturing processes. This integration is based upon advanced AI-based tools for decentralized decision-making and for secure and trusted data sharing in the global value. This paper presents the FASTEN IIoT Platform, which targets to provide a flexible, configurable, and open solution. The platform acts as an interface between the shop floor and the industry 4.0 advanced applications and solutions. Examples of these efforts comprise management, forecasting, optimization, and simulation, by harmonizing the heterogeneous characteristics of the data sources involved while meeting real-time requirements.

Objective: Simple measures of gait for routine clinical use could be useful when the complex gait analysis systems are not available. The aim of this study was to quantify asymmetry in children with spastic hemiplegia using a two-dimensional gait analysis by videography and to relate the asymmetry to motor function. Methods: Twenty-four children with spastic hemiplegia (19 males, 5 females; mean age 49 months [SD 5 months], range from 39 to 60 months) were assessed with a two-dimensional gait analysis by videography and the analyzed parameters were compared with normal values and with clinical and functional data. Results: There were significant differences in swing time (p = 0.002), stance time (p = 0.01) and stance/swing time ratio (p < 0.001). The comparison with the normal values described by Sutherland also demonstrated gait asymmetry. There was no direct relationship between the motor function and asymmetry but a score analysis for specific Gross Motor Function Measure items could quantify it in terms of age of gait acquisition. Children with more adequate muscle tone presented longer stance time in the involved limb than those with more spasticity (p = 0.03). Conclusions: These results suggest that the best performance is associated with the smallest asymmetry in this sample. Although two-dimensional gait analysis does not provide as much data as three dimensional gait analyses, we believe it can contribute significantly to the gait assessment of children with cerebral palsy.