Reflection of Challenges and Opportunities within the COVID-19 Pandemic to Include Biological Hazards into DRR Planning.

COVID-19 has reinforced the need to revisit the integration of health within disaster risk reduction (DRR) strategies for biological hazards in a system-wide approach. In November 2020, DRR experts attended the Asia-Pacific Partnership for Disaster Risk Reduction (APP-DRR) Forum to share progress and learnings in the areas of health system resilience, data management, residual risk management, risk communication, digital literacy, and knowledge product marketing. Advancements for health in DRR included the importance of multi-sectoral, multi-hazard action plans; adaptation to technological advancements in data collection, dissemination and protection; promoting the health and wellbeing of essential and nonprofessional workers; and improving inclusivity in digital literacy. COVID-19 has affected progress towards the Sustainable Development Goals (SDG) and created a unique opportunity within DRR to re-evaluate the adequacy of response mechanisms against concurrent, cascading or interacting risks of future biological hazards. Health emergency disaster risk management (Health-EDRM) is a new World Health Organization paradigm that includes DRR at intra-, inter- and multidisciplinary levels. Scientific advancement under Health-EDRM is necessary for health and non-health actors in DRR education and research. Continuous education on the multifaceted risk governance is a key to building awareness, capacity and accelerating towards achieving the international DRR and the SDG targets.

Muscle fatigue detection and treatment system driven by internet of things.

BACKGROUND: Internet of things is fast becoming the norm in everyday life, and integrating the Internet into medical treatment, which is increasing day by day, is of high utility to both clinical doctors and patients. While there are a number of different health-related problems encountered in daily life, muscle fatigue is a common problem encountered by many. METHODS: To facilitate muscle fatigue detection, a pulse width modulation (PWM) and ESP8266-based fatigue detection and recovery system is introduced in this paper to help alleviate muscle fatigue. The ESP8266 is employed as the main controller and communicator, and PWM technology is employed to achieve adaptive muscle recovery. Muscle fatigue can be detected by surface electromyography signals and monitored in real-time via a wireless network. RESULTS: With the help of the proposed system, human muscle fatigue status can be monitored in real-time, and the recovery vibration motor status can be optimized according to muscle activity state. DISCUSSION: Environmental factors had little effect on the response time and accuracy of the system, and the response time was stable between 1 and 2 s. As indicated by the consistent change of digital value, muscle fatigue was clearly diminished using this system. CONCLUSIONS: Experiments show that environmental factors have little effect on the response time and accuracy of the system. The response time is stably between 1 and 2 s, and, as indicated by the consistent change of digital value, our systems clearly diminishes muscle fatigue. Additionally, the experimental results show that the proposed system requires minimal power and is both sensitive and stable.