Computer Engineering, Brandenburg University of Technology, Cottbus-Senftenberg, 03046 Cottbus, Germany.
Sensors (Basel). 2022 Jul 15;22(14):5315. doi: 10.3390/s22145315.
The recent pandemic outbreak proved social distancing effective in helping curb the spread of SARS-CoV-2 variants along with the wearing of masks and hand gloves in hospitals and assisted living environments. Health delivery personnel having undergone training regarding the handling of patients suffering from Corona infection have been stretched. Administering injections involves unavoidable person to person contact. In this circumstance, the spread of bodily fluids and consequently the Coronavirus become eminent, leading to an upsurge of infection rates among nurses and doctors. This makes enforced home office practices and telepresence through humanoid robots a viable alternative. In providing assistance to further reduce contact with patients during vaccinations, a software module has been designed, developed, and implemented on a Pepper robot that estimates the pose of a patient, identifies an injection spot, and raises an arm to deliver the vaccine dose on a bare shoulder. Implementation was done using the QiSDK in an android integrated development environment with a custom Python wrapper. Tests carried out yielded positive results in under 60 s with an 80% success rate, and exposed some ambient lighting discrepancies. These discrepancies can be solved in the near future, paving a new way for humans to get vaccinated.
最近的大流行爆发证明,社交距离在帮助遏制 SARS-CoV-2 变种的传播方面非常有效,同时在医院和辅助生活环境中佩戴口罩和手套也是如此。接受过处理新冠感染患者培训的医疗服务人员已经不堪重负。注射涉及不可避免的人与人之间的接触。在这种情况下,体液传播和由此产生的冠状病毒变得非常明显,导致护士和医生的感染率上升。这使得强制在家办公和通过人形机器人远程呈现成为一种可行的替代方案。为了在接种疫苗时进一步减少与患者的接触,我们设计、开发并在 Pepper 机器人上实现了一个软件模块,该模块估计患者的姿势,识别注射点,并抬起手臂在裸露的肩膀上接种疫苗剂量。实施是在带有自定义 Python 包装器的安卓集成开发环境中使用 QiSDK 完成的。测试在 60 秒内得出了积极的结果,成功率为 80%,并暴露了一些环境光照差异。这些差异可以在不久的将来得到解决,为人类接种疫苗开辟了一条新途径。