InjectMeAI-Software Module of an Autonomous Injection Humanoid.

Area of Science:

• Robotics
• Infectious Disease Control
• Healthcare Technology

Background:

• The COVID-19 pandemic highlighted risks to healthcare workers from patient contact, particularly during procedures like vaccinations.
• Social distancing, masks, and gloves were crucial but insufficient to prevent transmission among stretched healthcare personnel.
• The need for innovative solutions to minimize person-to-person contact in healthcare settings became evident.

Purpose of the Study:

• To develop and implement a robotic system for automated vaccine delivery, reducing direct contact between healthcare workers and patients.
• To assess the feasibility and effectiveness of a humanoid robot in performing vaccination tasks.
• To explore telepresence and robotics as alternatives for healthcare delivery during pandemics.

Main Methods:

• A software module was designed and developed for a Pepper humanoid robot.
• The system utilized the QiSDK within an Android IDE, incorporating a Python wrapper.
• The robot was programmed to estimate patient pose, identify an injection site, and simulate vaccine delivery to the shoulder.

Main Results:

• The robotic system achieved positive results in under 60 seconds with an 80% success rate in tests.
• The implementation demonstrated the potential for robots to assist in vaccination procedures.
• Ambient lighting conditions were identified as a factor affecting performance, indicating areas for future improvement.

Conclusions:

• Humanoid robots offer a viable alternative for reducing infection transmission risks during vaccinations.
• Further development can overcome current limitations, paving the way for automated and safer vaccination processes.
• Robotic assistance in healthcare delivery can enhance safety for both patients and providers, especially during infectious disease outbreaks.