Christian Werner1, Nikos Kardaris2, Petros Koutras3, Athanasia Zlatintsi4, Petros Maragos5, Jürgen M Bauer6, Klaus Hauer7. 1. Center for Geriatric Medicine, Heidelberg University, Heidelberg, Germany; Agaplesion Bethanien Hospital Heidelberg, Geriatric Center at the Heidelberg University, Heidelberg, Germany. Electronic address: christian.werner@bethanien-heidelberg.de. 2. Institute of Communication and Computer Systems (ICCS), National Technical University of Athens, Athens, Greece. Electronic address: nkardaris@mail.ntua.gr. 3. Institute of Communication and Computer Systems (ICCS), National Technical University of Athens, Athens, Greece. Electronic address: pkoutras@cs.ntua.gr. 4. Institute of Communication and Computer Systems (ICCS), National Technical University of Athens, Athens, Greece. Electronic address: nzlat@cs.ntua.gr. 5. Institute of Communication and Computer Systems (ICCS), National Technical University of Athens, Athens, Greece. Electronic address: maragos@cs.ntua.gr. 6. Center for Geriatric Medicine, Heidelberg University, Heidelberg, Germany; Agaplesion Bethanien Hospital Heidelberg, Geriatric Center at the Heidelberg University, Heidelberg, Germany. Electronic address: juergen.bauer@bethanien-heidelberg.de. 7. Agaplesion Bethanien Hospital Heidelberg, Geriatric Center at the Heidelberg University, Heidelberg, Germany. Electronic address: khauer@bethanien-heidelberg.de.
Abstract
BACKGROUND: Gesture-based human-robot interaction (HRI) depends on the technical performance of the robot-integrated gesture recognition system (GRS) and on the gestural performance of the robot user, which has been shown to be rather low in older adults. Training of gestural commands (GCs) might improve the quality of older users' input for gesture-based HRI, which in turn may lead to an overall improved HRI. OBJECTIVE: To evaluate the effects of a user training on gesture-based HRI between an assistive bathing robot and potential elderly robot users. METHODS: Twenty-five older adults with bathing disability participated in this quasi-experimental, single-group, pre-/post-test study and underwent a specific user training (10-15 min) on GCs for HRI with the assistive bathing robot. Outcomes measured before and after training included participants' gestural performance assessed by a scoring method of an established test of gesture production (TULIA) and sensor-based gestural performance (SGP) scores derived from the GRS-recorded data, and robot's command recognition rate (CRR). RESULTS: Gestural performance (TULIA = +57.1 ± 56.2 %, SGP scores = +41.1 ± 74.4 %) and CRR (+31.9 ± 51.2 %) significantly improved over training (p < .001). Improvements in gestural performance and CRR were highly associated with each other (r = 0.80-0.81, p < .001). Participants with lower initial gestural performance and higher gerontechnology anxiety benefited most from the training. CONCLUSIONS: Our study highlights that training in gesture-based HRI with an assistive bathing robot is highly beneficial for the quality of older users' GCs, leading to higher CRRs of the robot-integrated GRS, and thus to an overall improved HRI.
BACKGROUND: Gesture-based human-robot interaction (HRI) depends on the technical performance of the robot-integrated gesture recognition system (GRS) and on the gestural performance of the robot user, which has been shown to be rather low in older adults. Training of gestural commands (GCs) might improve the quality of older users' input for gesture-based HRI, which in turn may lead to an overall improved HRI. OBJECTIVE: To evaluate the effects of a user training on gesture-based HRI between an assistive bathing robot and potential elderly robot users. METHODS: Twenty-five older adults with bathing disability participated in this quasi-experimental, single-group, pre-/post-test study and underwent a specific user training (10-15 min) on GCs for HRI with the assistive bathing robot. Outcomes measured before and after training included participants' gestural performance assessed by a scoring method of an established test of gesture production (TULIA) and sensor-based gestural performance (SGP) scores derived from the GRS-recorded data, and robot's command recognition rate (CRR). RESULTS: Gestural performance (TULIA = +57.1 ± 56.2 %, SGP scores = +41.1 ± 74.4 %) and CRR (+31.9 ± 51.2 %) significantly improved over training (p < .001). Improvements in gestural performance and CRR were highly associated with each other (r = 0.80-0.81, p < .001). Participants with lower initial gestural performance and higher gerontechnology anxiety benefited most from the training. CONCLUSIONS: Our study highlights that training in gesture-based HRI with an assistive bathing robot is highly beneficial for the quality of older users' GCs, leading to higher CRRs of the robot-integrated GRS, and thus to an overall improved HRI.