Background Hospital cabins are a part and parcel of the healthcare system. Most patients admitted in hospital cabins reside in bedridden and immobile conditions. Though different kinds of systems exist to aid such patients, most of them focus on specific tasks like calling for emergencies, monitoring patient health, etc. while the patients’ limitations are ignored. Though some patient interaction systems have been developed, only singular options like touch, hand gesture or voice based interaction were provided which may not be usable for bedridden and immobile patients. Methods At first, we reviewed the existing literature to explore the prevailing healthcare and interaction systems developed for bedridden and immobile patients. Then, a requirements elicitation study was conducted through semi-structured interviews. Afterwards, design goals were established to address the requirements. Based on these goals and by using computer vision and deep learning technologies, a hospital cabin control system having multimodal interactions facility was designed and developed for hospital admitted, bedridden and immobile patients. Finally, the system was evaluated through an experiment replicated with 12 hospital admitted patients to measure its effectiveness, usability and efficiency. Results As outcomes, firstly, a set of user-requirements were identified for hospital admitted patients and healthcare practitioners. Secondly, a hospital cabin control system was designed and developed that supports multimodal interactions for bedridden and immobile hospital admitted patients which includes (a) Hand gesture based interaction for moving a cursor with hand and showing hand gesture for clicking, (b) Nose teeth based interaction where nose is used for moving a cursor and teeth is used for clicking and (c) Voice based interaction for executing tasks using specific voice commands. Finally, the evaluation results showed that the system is efficient, effective and usable to the focused users with 100% success rate, reasonable number of attempts and task completion time. Conclusion In the resultant system, Deep Learning has been incorporated to facilitate multimodal interaction for enhancing accessibility. Thus, the developed system along with its evaluation results and the identified requirements provides a promising solution for the prevailing crisis in the healthcare sector. Trial Registration Not Applicable.
During the COVID-19 pandemic, surface disinfection using prevailing chemical disinfection methods had several limitations. Due to cost-inefficiency and the inability to disinfect shaded places, static UVC lamps cannot address these limitations properly. Moreover, the average market price of the prevailing UVC robots is huge, approximately 55,165 USD. In this research firstly, a requirement elicitation study was conducted using a semi-structured interview approach to reveal the requirements to develop a cost-effective UVC robot. Secondly, a semi-autonomous robot named UVC-PURGE was developed based on the revealed requirements. Thirdly, a two-phased evaluation study was undertaken to validate the effectiveness of UVC-PURGE to inactivate the SARS-CoV-2 virus and the capability of semi-autonomous navigation in the first phase and to evaluate the usability of the system through a hybrid approach of SUPR-Q forms and subjective evaluation of the user feedback in the second phase. Pre-treatment swab testing revealed the presence of both Gram-positive and Gram-Negative bacteria at 17 out of 20 test surfaces in the conducted tests. After the UVC irradiation of the robot, the microbial load was detected in only 2 (1D and 1H) out of 17 test surfaces with significant reductions (95.33% in 1D and 90.9% in 1H) of microbial load. Moreover, the usability evaluation yields an above-average SUPR-Q score of 81.91% with significant scores in all the criteria (usability, trust, loyalty, and appearance) and the number of positive themes from the subjective evaluation using thematic analysis is twice the number of negative themes. Additionally, compared with the prevailing UVC disinfection robots in the market, UVC-PURGE is cost-effective with a price of less than 800 USD. Moreover, small form factor along with the real time camera feedback in the developed system helps the user to navigate in congested places easily. The developed robot can be used in any indoor environment in this prevailing pandemic situation and it can also provide cost-effective disinfection in medical facilities against the long-term residual effect of COVID-19 in the post-pandemic era.INDEX TERMS COVID-19, UVC robot, medical robotics, infection control, disinfection methods.
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