Purpose: Patient-specific quality assurance (PSQA) requires manual operation of different workstations, which is time-consuming and error-prone. Therefore, developing automated solutions to improve efficiency and accu...Purpose: Patient-specific quality assurance (PSQA) requires manual operation of different workstations, which is time-consuming and error-prone. Therefore, developing automated solutions to improve efficiency and accuracy is a priority. The purpose of this study was to develop a general software interface with scripting on a human interactive device (HID) for improving the efficiency and accuracy of manual quality assurance (QA) procedures. Methods: As an initial application, we aimed to automate our PSQA workflow that involves Varian Eclipse treatment planning system, Elekta MOSAIQ oncology information system and PTW Verisoft application. A general platform, the AutoFrame interface with two imbedded subsystems—the AutoFlow and the PyFlow, was developed with a scripting language for automating human operations of aforementioned systems. The interface included three functional modules: GUI module, UDF script interpreter and TCP/IP communication module. All workstations in the PSQA process were connected, and most manual operations were automated by AutoFrame sequentially or in parallel. Results: More than 20 PSQA tasks were performed both manually and using the developed AutoFrame interface. On average, 175 (±12) manual operations of the PSQA procedure were eliminated and performed by the automated process. The time to complete a PSQA task was 8.23 (±0.78) minutes for the automated workflow, in comparison to 13.91 (±3.01) minutes needed for manual operations. Conclusion: We have developed the AutoFrame interface framework that successfully automated our PSQA procedure, and significantly reduced the time, human (control/clicking/typing) errors, and operators’ stress. Future work will focus on improving the system’s flexibility and stability and extending its operations to other QA procedures.展开更多
The prosperous evolution of conductive hydrogel-based skin sensors is attract-ing tremendous attention nowadays.Nevertheless,it remains a great challenge to simultaneously integrate excellent mechanical strength,desir...The prosperous evolution of conductive hydrogel-based skin sensors is attract-ing tremendous attention nowadays.Nevertheless,it remains a great challenge to simultaneously integrate excellent mechanical strength,desirable electrical conduc-tivity,admirable sensing performance,and brilliant healability in hydrogel-based skin sensors for high-performance diagnostic healthcare sensing and wearable human-machine interface,as well as robust photothermal performance for promptly intelligent photothermal therapy followed by the medical diagnosis and superior electromagnetic interference(EMI)shielding performance for personal protec-tion.Herein,aflexible healable MXene hydrogel-based skin sensor is prepared through a delicate combination of MXene(Ti_(3)C_(2)T_(x))nanosheets network with the polymeric network.The as-prepared skin sensor is featured with significantly enhanced mechanical,conducting,and sensing performances,along with robust self-healability,good biocompatibility,and reliable injectability,enabling ultrasensitive human motion monitoring and teeny electrophysiological signals sensing.As a fron-tier technology in artificial intelligence,machine learning can facilitate to efficiently and precisely identify the electromyography signals produced by various human motions(such as variablefinger gestures)with up to 99.5%accuracy,affirming the reliability of the machine learning-assisted gesture identification with great poten-tial in smart personalized healthcare and human-machine interaction.Moreover,the MXene hydrogel-based skin sensor displays prominent EMI shielding performance,demonstrating the great promise of effective personal protection.展开更多
Flexible wearables have attracted extensive interests for personal human motion sensing,intelligent disease diagnosis,and multifunctional electronic skins.How-ever,the reported flexible sensors,mostly exhibited narrow...Flexible wearables have attracted extensive interests for personal human motion sensing,intelligent disease diagnosis,and multifunctional electronic skins.How-ever,the reported flexible sensors,mostly exhibited narrow detection range,low sensitivity,limited degradability to aggravate environmental pollution from vast electronic wastes,and poor antibacterial performance to hardly improve skin dis-comfort and skin inflammation from bacterial growth under long-term wearing.Herein,bioinspired from human skin featuring highly sensitive tactile sensation with spinous microstructures for amplifying sensing sensitivity between epidermis and dermis,a wearable antibacterial degradable electronics is prepared from degrad-able elastomeric substrate with MXene-coated spinous microstructures templated from lotus leaf assembled with the interdigitated electrode.The degradable elas-tomer is facilely obtained with tunable modulus to match the modulus of human skin with improved hydrophilicity for rapid degradation.The as-obtained sensor displays ultra-low detection limit(0.2 Pa),higher sensitivity(up to 540.2 kPa^(-1)),outstand-ing cycling stability(>23,000 cycles),a wide detection range,robust degradability,and excellent antibacterial capability.Facilitated by machine learning,the collected sensing signals from the integrated sensors on volunteer's fingers to the related American Sign Language are effectively recognized with an accuracy up to 99%,showing excellent potential in wireless human movement sensing and smart machine learning-enabled human-machine interaction.展开更多
文摘Purpose: Patient-specific quality assurance (PSQA) requires manual operation of different workstations, which is time-consuming and error-prone. Therefore, developing automated solutions to improve efficiency and accuracy is a priority. The purpose of this study was to develop a general software interface with scripting on a human interactive device (HID) for improving the efficiency and accuracy of manual quality assurance (QA) procedures. Methods: As an initial application, we aimed to automate our PSQA workflow that involves Varian Eclipse treatment planning system, Elekta MOSAIQ oncology information system and PTW Verisoft application. A general platform, the AutoFrame interface with two imbedded subsystems—the AutoFlow and the PyFlow, was developed with a scripting language for automating human operations of aforementioned systems. The interface included three functional modules: GUI module, UDF script interpreter and TCP/IP communication module. All workstations in the PSQA process were connected, and most manual operations were automated by AutoFrame sequentially or in parallel. Results: More than 20 PSQA tasks were performed both manually and using the developed AutoFrame interface. On average, 175 (±12) manual operations of the PSQA procedure were eliminated and performed by the automated process. The time to complete a PSQA task was 8.23 (±0.78) minutes for the automated workflow, in comparison to 13.91 (±3.01) minutes needed for manual operations. Conclusion: We have developed the AutoFrame interface framework that successfully automated our PSQA procedure, and significantly reduced the time, human (control/clicking/typing) errors, and operators’ stress. Future work will focus on improving the system’s flexibility and stability and extending its operations to other QA procedures.
基金National Natural Science Foundation of China,Grant/Award Number:52222303Biomedical Translational Engineering Research Center of BUCT-CJFH,Grant/Award Number:XK2022-03。
文摘The prosperous evolution of conductive hydrogel-based skin sensors is attract-ing tremendous attention nowadays.Nevertheless,it remains a great challenge to simultaneously integrate excellent mechanical strength,desirable electrical conduc-tivity,admirable sensing performance,and brilliant healability in hydrogel-based skin sensors for high-performance diagnostic healthcare sensing and wearable human-machine interface,as well as robust photothermal performance for promptly intelligent photothermal therapy followed by the medical diagnosis and superior electromagnetic interference(EMI)shielding performance for personal protec-tion.Herein,aflexible healable MXene hydrogel-based skin sensor is prepared through a delicate combination of MXene(Ti_(3)C_(2)T_(x))nanosheets network with the polymeric network.The as-prepared skin sensor is featured with significantly enhanced mechanical,conducting,and sensing performances,along with robust self-healability,good biocompatibility,and reliable injectability,enabling ultrasensitive human motion monitoring and teeny electrophysiological signals sensing.As a fron-tier technology in artificial intelligence,machine learning can facilitate to efficiently and precisely identify the electromyography signals produced by various human motions(such as variablefinger gestures)with up to 99.5%accuracy,affirming the reliability of the machine learning-assisted gesture identification with great poten-tial in smart personalized healthcare and human-machine interaction.Moreover,the MXene hydrogel-based skin sensor displays prominent EMI shielding performance,demonstrating the great promise of effective personal protection.
基金National Natural Science Foundation of China,Grant/Award Numbers:52222303,51973008Joint Project of BRC-BC(Biomedical Translational Engineering Research Center of BUCT-CJFH),Grant/Award Number:XK2022-03Fundamental Research Funds for the Central Universities。
文摘Flexible wearables have attracted extensive interests for personal human motion sensing,intelligent disease diagnosis,and multifunctional electronic skins.How-ever,the reported flexible sensors,mostly exhibited narrow detection range,low sensitivity,limited degradability to aggravate environmental pollution from vast electronic wastes,and poor antibacterial performance to hardly improve skin dis-comfort and skin inflammation from bacterial growth under long-term wearing.Herein,bioinspired from human skin featuring highly sensitive tactile sensation with spinous microstructures for amplifying sensing sensitivity between epidermis and dermis,a wearable antibacterial degradable electronics is prepared from degrad-able elastomeric substrate with MXene-coated spinous microstructures templated from lotus leaf assembled with the interdigitated electrode.The degradable elas-tomer is facilely obtained with tunable modulus to match the modulus of human skin with improved hydrophilicity for rapid degradation.The as-obtained sensor displays ultra-low detection limit(0.2 Pa),higher sensitivity(up to 540.2 kPa^(-1)),outstand-ing cycling stability(>23,000 cycles),a wide detection range,robust degradability,and excellent antibacterial capability.Facilitated by machine learning,the collected sensing signals from the integrated sensors on volunteer's fingers to the related American Sign Language are effectively recognized with an accuracy up to 99%,showing excellent potential in wireless human movement sensing and smart machine learning-enabled human-machine interaction.
