| 1. |
- Ahmed, Mobyen Uddin, 1976-, et al.
(författare)
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A case-based patient identification system using pulseoximeter and a personalized health profile
- 2012
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Ingår i: Proceedings of the ICCBR 2012 Workshops. - Lyon, France. ; , s. 117-128
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Konferensbidrag (refereegranskat)abstract
- This paper proposes a case-based system framework in order to identify patient using their health parameters taken with physiological sensors. It combines a personalized health profiling protocol with a Case-Based Reasoning (CBR) approach. The personalized health profiling helps to determine a number of individual parameters which are important inputs for a clinician to make the final diagnosis and treatment plan. The proposed system uses a pulse oximeter that measures pulse rate and blood oxygen saturation. The measurements are taken through an android application in a smart phone which is connected with the pulseoximeter and bluetooth communication. The CBR approach helps clinicians to make a diagnosis, classification and treatment plan by retrieving the most similar previous case. The case may also be used to follow the treatment progress. Here, the cases are formulated with person’s contextual information and extracted features from sensor signal measurements. The features are extracted considering three domain analysis:1) time domain features using statistical measurement, 2) frequency domain features applying Fast Fourier Transform (FFT), and 3) time-frequency domain features applying Discrete Wavelet Transform (DWT). The initial result is acceptable that shows the advancement of the system while combining the personalized health profiling together with CBR.
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| 2. |
- Ahmed, Mobyen Uddin, 1976-, et al.
(författare)
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Physical Activity Classification for Elderly based on Pulse Rate
- 2013
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Ingår i: Studies in Health Technology and Informatics, vol. 189. - : IOS Press. - 9781614992677 ; , s. 152-157
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Konferensbidrag (refereegranskat)abstract
- Physical activity is one of the key components for elderly in order to be actively ageing. However, it is difficult to differentiate and identify the body movement and actual physical activity using only accelerometer measurement. Therefore, this paper presents an application of case-based retrieval classification scheme to classify the physical activity of elderly based on pulse rate measurements. Here, case-based retrieval approach used the features extracted from both time and frequency domain. The evaluation result shows the best accuracy performance while considering the combination of time and frequency domain features. According to the evaluation result while considering the control measurements, the sensitivity, specificity and overall accuracy are achieved as 95%, 96% and 96% respectively. Considering the test dataset, the system was succeeded to identify 13 physical activities out of 16 i.e. the percentage of the correctness was 81%.
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| 3. |
- Akalin, Neziha, 1988-, et al.
(författare)
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A Taxonomy of Factors Influencing Perceived Safety in Human–Robot Interaction
- 2023
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Ingår i: International Journal of Social Robotics. - : Springer Science and Business Media B.V.. - 1875-4791 .- 1875-4805.
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Tidskriftsartikel (refereegranskat)abstract
- Safety is a fundamental prerequisite that must be addressed before any interaction of robots with humans. Safety has been generally understood and studied as the physical safety of robots in human–robot interaction, whereas how humans perceive these robots has received less attention. Physical safety is a necessary condition for safe human–robot interaction. However, it is not a sufficient condition. A robot that is safe by hardware and software design can still be perceived as unsafe. This article focuses on perceived safety in human–robot interaction. We identified six factors that are closely related to perceived safety based on the literature and the insights obtained from our user studies. The identified factors are the context of robot use, comfort, experience and familiarity with robots, trust, the sense of control over the interaction, and transparent and predictable robot actions. We then made a literature review to identify the robot-related factors that influence perceived safety. Based the literature, we propose a taxonomy which includes human-related and robot-related factors. These factors can help researchers to quantify perceived safety of humans during their interactions with robots. The quantification of perceived safety can yield computational models that would allow mitigating psychological harm.
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| 4. |
- Akalin, Neziha, 1988-, et al.
(författare)
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An Evaluation Tool of the Effect of Robots in Eldercare on the Sense of Safety and Security
- 2017
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Ingår i: Social Robotics. - Cham : Springer International Publishing. - 9783319700229 - 9783319700212 ; , s. 628-637
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Konferensbidrag (refereegranskat)abstract
- The aim of the study presented in this paper is to develop a quantitative evaluation tool of the sense of safety and security for robots in eldercare. By investigating the literature on measurement of safety and security in human-robot interaction, we propose new evaluation tools. These tools are semantic differential scale questionnaires. In experimental validation, we used the Pepper robot, programmed in the way to exhibit social behaviors, and constructed four experimental conditions varying the degree of the robot’s non-verbal behaviors from no gestures at all to full head and hand movements. The experimental results suggest that both questionnaires (for the sense of safety and the sense of security) have good internal consistency.
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| 5. |
- Akalin, Neziha, 1988-, et al.
(författare)
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Do you feel safe with your robot? Factors influencing perceived safety in human-robot interaction based on subjective and objective measures
- 2022
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Ingår i: International journal of human-computer studies. - : Academic Press. - 1071-5819 .- 1095-9300. ; 158
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Tidskriftsartikel (refereegranskat)abstract
- Safety in human-robot interaction can be divided into physical safety and perceived safety, where the later is still under-addressed in the literature. Investigating perceived safety in human-robot interaction requires a multidisciplinary perspective. Indeed, perceived safety is often considered as being associated with several common factors studied in other disciplines, i.e., comfort, predictability, sense of control, and trust. In this paper, we investigated the relationship between these factors and perceived safety in human-robot interaction using subjective and objective measures. We conducted a two-by-five mixed-subjects design experiment. There were two between-subjects conditions: the faulty robot was experienced at the beginning or the end of the interaction. The five within-subjects conditions correspond to (1) baseline, and the manipulations of robot behaviors to stimulate: (2) discomfort, (3) decreased perceived safety, (4) decreased sense of control and (5) distrust. The idea of triggering a deprivation of these factors was motivated by the definition of safety in the literature where safety is often defined by the absence of it. Twenty-seven young adult participants took part in the experiments. Participants were asked to answer questionnaires that measure the manipulated factors after within-subjects conditions. Besides questionnaire data, we collected objective measures such as videos and physiological data. The questionnaire results show a correlation between comfort, sense of control, trust, and perceived safety. Since these factors are the main factors that influence perceived safety, they should be considered in human-robot interaction design decisions. We also discuss the effect of individual human characteristics (such as personality and gender) that they could be predictors of perceived safety. We used the physiological signal data and facial affect from videos for estimating perceived safety where participants’ subjective ratings were utilized as labels. The data from objective measures revealed that the prediction rate was higher from physiological signal data. This paper can play an important role in the goal of better understanding perceived safety in human-robot interaction.
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| 6. |
- Akalin, Neziha, 1988-, et al.
(författare)
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Enhancing Social Human-Robot Interaction with Deep Reinforcement Learning.
- 2018
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Ingår i: Proc. FAIM/ISCA Workshop on Artificial Intelligence for Multimodal Human Robot Interaction, 2018. - : MHRI. ; , s. 48-50
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Konferensbidrag (refereegranskat)abstract
- This research aims to develop an autonomous social robot for elderly individuals. The robot will learn from the interaction and change its behaviors in order to enhance the interaction and improve the user experience. For this purpose, we aim to use Deep Reinforcement Learning. The robot will observe the user’s verbal and nonverbal social cues by using its camera and microphone, the reward will be positive valence and engagement of the user.
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| 7. |
- Akalin, Neziha, 1988-, et al.
(författare)
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Evaluating the Sense of Safety and Security in Human–Robot Interaction with Older People
- 2019
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Ingår i: Social Robots: Technological, Societal and Ethical Aspects of Human-Robot Interaction. - Cham : Springer, Cham. - 9783030171063 - 9783030171070 ; , s. 237-264
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Bokkapitel (refereegranskat)abstract
- For many applications where interaction between robots and older people takes place, safety and security are key dimensions to consider. ‘Safety’ refers to a perceived threat of physical harm, whereas ‘security’ is a broad term which refers to many aspects related to health, well-being, and aging. This chapter presents a quantitative evaluation tool of the sense of safety and security for robots in elder care. By investigating the literature on measurement of safety and security in human–robot interaction, we propose new evaluation tools specially tailored to assess interaction between robots and older people.
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| 8. |
- Akalin, Neziha, 1988-, et al.
(författare)
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The Influence of Feedback Type in Robot-Assisted Training
- 2019
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Ingår i: Multimodal Technologies and Interaction. - : Multidisciplinary Digital Publishing Institute. - 2414-4088. ; 3:4
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Tidskriftsartikel (refereegranskat)abstract
- Robot-assisted training, where social robots can be used as motivational coaches, provides an interesting application area. This paper examines how feedback given by a robot agent influences the various facets of participant experience in robot-assisted training. Specifically, we investigated the effects of feedback type on robot acceptance, sense of safety and security, attitude towards robots and task performance. In the experiment, 23 older participants performed basic arm exercises with a social robot as a guide and received feedback. Different feedback conditions were administered, such as flattering, positive and negative feedback. Our results suggest that the robot with flattering and positive feedback was appreciated by older people in general, even if the feedback did not necessarily correspond to objective measures such as performance. Participants in these groups felt better about the interaction and the robot.
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| 9. |
- Akalin, Neziha, 1988-, et al.
(författare)
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The Relevance of Social Cues in Assistive Training with a Social Robot
- 2018
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Ingår i: 10th International Conference on Social Robotics, ICSR 2018, Proceedings. - Cham : Springer. - 9783030052034 - 9783030052041 ; , s. 462-471
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Konferensbidrag (refereegranskat)abstract
- This paper examines whether social cues, such as facial expressions, can be used to adapt and tailor a robot-assisted training in order to maximize performance and comfort. Specifically, this paper serves as a basis in determining whether key facial signals, including emotions and facial actions, are common among participants during a physical and cognitive training scenario. In the experiment, participants performed basic arm exercises with a social robot as a guide. We extracted facial features from video recordings of participants and applied a recursive feature elimination algorithm to select a subset of discriminating facial features. These features are correlated with the performance of the user and the level of difficulty of the exercises. The long-term aim of this work, building upon the work presented here, is to develop an algorithm that can eventually be used in robot-assisted training to allow a robot to tailor a training program based on the physical capabilities as well as the social cues of the users.
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| 10. |
- Alirezaie, Marjan, 1980-, et al.
(författare)
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An ontology-based context-aware system for smart homes : E-care@home
- 2017
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Ingår i: Sensors. - Basel : MDPI AG. - 1424-8220. ; 17:7
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Tidskriftsartikel (refereegranskat)abstract
- Smart home environments have a significant potential to provide for long-term monitoring of users with special needs in order to promote the possibility to age at home. Such environments are typically equipped with a number of heterogeneous sensors that monitor both health and environmental parameters. This paper presents a framework called E-care@home, consisting of an IoT infrastructure, which provides information with an unambiguous, shared meaning across IoT devices, end-users, relatives, health and care professionals and organizations. We focus on integrating measurements gathered from heterogeneous sources by using ontologies in order to enable semantic interpretation of events and context awareness. Activities are deduced using an incremental answer set solver for stream reasoning. The paper demonstrates the proposed framework using an instantiation of a smart environment that is able to perform context recognition based on the activities and the events occurring in the home.
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