Human-machine cooperation in healthcare
People are increasingly interacting with intelligent technology, as the real and digital worlds become intertwined. An EU-funded project is working to bring new forms of human-machine collaboration into real-life educational settings for healthcare providers that will benefit students, trainers and patients.
© zapp2photo #170499375 2019, source:stock.adobe.com
People and machines can complement each others specific skills and capabilities to achieve goals neither could accomplish alone. Scientists in a number of fields are developing hybrid systems that will enable people and machines to work together more efficiently.
The aim of the EU-funded SMARTNURSE project is to identify for further development technologies enabling human-computer cooperation that can be used in educational settings. The project builds on trials already carried out in nurse-training scenarios.
In one such trial, carried out by a European university, student nurses wore a 'smart assistant' featuring a head-mounted display during the simulated resuscitation of a non-responsive patient.
This wearable smart assistant provided a range of information, on demand, via the display, including suggestions about how to proceed, instant answers to a variety of medical questions, and information about hospital regulations. The headset can also assess the performance of specific activities, such as chest compression, providing feedback in real time.
Complex and subtle actions
Other research under SMARTNURSE has demonstrated the use of a sensor-equipped 'smart watch'. The device documents patient-care activities and provides training in cardiopulmonary resuscitation. This work demonstrated that even a single sensor node worn on a nurse's wrist can recognise and assess complex and sometimes subtle actions.
SMARTNURSE researchers are determining whether some elements from these and similar trials might be suitable for transference into real-life educational practices. Of particular interest are technical, regulatory, financial and social issues linked to the use of such systems in nursing schools.
The project has already generated significant interest within the healthcare community. The project team believes sensor-based activity recognition combined with novel interaction techniques can benefit students, trainers and, ultimately, patients. .