Pub Date : 2020-09-01DOI: 10.1109/ICHMS49158.2020.9209477
A. Chella, Francesco Lanza, A. Pipitone, V. Seidita
Giving the robot a “human” inner life, such as the capability to think about itself and to understand what the other team members are doing, would increase the efficiency of trustworthy interactions with the other members of the team. Our long-term research goal is to provide the robot with a computational model of inner life helping the robot to reason about itself, its capabilities, its environment and its teammates. Robot inner speech is a part of the research goal. In this paper, we summarize the results obtained in this direction.
{"title":"The Inner Life of a Robot in Human-Robot Teaming","authors":"A. Chella, Francesco Lanza, A. Pipitone, V. Seidita","doi":"10.1109/ICHMS49158.2020.9209477","DOIUrl":"https://doi.org/10.1109/ICHMS49158.2020.9209477","url":null,"abstract":"Giving the robot a “human” inner life, such as the capability to think about itself and to understand what the other team members are doing, would increase the efficiency of trustworthy interactions with the other members of the team. Our long-term research goal is to provide the robot with a computational model of inner life helping the robot to reason about itself, its capabilities, its environment and its teammates. Robot inner speech is a part of the research goal. In this paper, we summarize the results obtained in this direction.","PeriodicalId":132917,"journal":{"name":"2020 IEEE International Conference on Human-Machine Systems (ICHMS)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121117562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICHMS49158.2020.9209378
Douglas W. Lee, E. Bass, C. Pankok
Understanding human operator timeline requirements can inform system requirements. This research defines an approach involving the development of a timeline of events for the human operators and supporting technology in order to complete the activities of interest. The approach is intended for evaluating systems for which real-world data are sparse and the required data collection may be costly. Timeline requirements are expressed as relationships between events and parameters affecting the timing for events. To make predictions, actual timeline parameters can be estimated from the literature when available or new human subject experiments can be designed to obtain them. The method described is highlighted using an air traffic conflict case study of non-cooperative aircraft (aircraft that do not share state data).
{"title":"Developing Operator-in-the-loop Timeline Requirements with a Case Study involving Non-cooperative Encounters with Unmanned Aircraft","authors":"Douglas W. Lee, E. Bass, C. Pankok","doi":"10.1109/ICHMS49158.2020.9209378","DOIUrl":"https://doi.org/10.1109/ICHMS49158.2020.9209378","url":null,"abstract":"Understanding human operator timeline requirements can inform system requirements. This research defines an approach involving the development of a timeline of events for the human operators and supporting technology in order to complete the activities of interest. The approach is intended for evaluating systems for which real-world data are sparse and the required data collection may be costly. Timeline requirements are expressed as relationships between events and parameters affecting the timing for events. To make predictions, actual timeline parameters can be estimated from the literature when available or new human subject experiments can be designed to obtain them. The method described is highlighted using an air traffic conflict case study of non-cooperative aircraft (aircraft that do not share state data).","PeriodicalId":132917,"journal":{"name":"2020 IEEE International Conference on Human-Machine Systems (ICHMS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124885013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICHMS49158.2020.9209438
William I. N. Sealy, K. Feigh
Decision support systems (DSS) are valuable tools for information management and decision making guidance, and are vital in decision environments that are inherently dynamic or that leverage a time pressure on the operator. In this work, we detail the application and effectiveness of several decision support techniques in a time-limited decision environment. These techniques, namely heuristic (HIA) and optimal experimental design (OED) information acquisition/restriction, represent heuristic and probabilistic approaches to decision support. In addition to these techniques, participants were given a selection of tasks that allowed free acquisition of information in order to determine their default behavior. Results show that all heuristic and one of the two probabilistic decision support strategies increased accuracy, and that all strategies resulted in faster decision making. Furthermore, free acquisition analysis indicates that participants default to probabilistic strategies even during extended periods of poor performance, which complicates the discussion around “optimal” decision support strategy.
{"title":"Information Modification for Time-Limited Decision Making","authors":"William I. N. Sealy, K. Feigh","doi":"10.1109/ICHMS49158.2020.9209438","DOIUrl":"https://doi.org/10.1109/ICHMS49158.2020.9209438","url":null,"abstract":"Decision support systems (DSS) are valuable tools for information management and decision making guidance, and are vital in decision environments that are inherently dynamic or that leverage a time pressure on the operator. In this work, we detail the application and effectiveness of several decision support techniques in a time-limited decision environment. These techniques, namely heuristic (HIA) and optimal experimental design (OED) information acquisition/restriction, represent heuristic and probabilistic approaches to decision support. In addition to these techniques, participants were given a selection of tasks that allowed free acquisition of information in order to determine their default behavior. Results show that all heuristic and one of the two probabilistic decision support strategies increased accuracy, and that all strategies resulted in faster decision making. Furthermore, free acquisition analysis indicates that participants default to probabilistic strategies even during extended periods of poor performance, which complicates the discussion around “optimal” decision support strategy.","PeriodicalId":132917,"journal":{"name":"2020 IEEE International Conference on Human-Machine Systems (ICHMS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114944249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICHMS49158.2020.9209463
Xia He, Xiaoguang Lin, Di Wu, Juan Wang
Classification, which is one of the most powerful approaches to filter valuable information from big data, is a typical supervised learning method of machine learning. In many real applications, the collected data may contain many redundant features and have some missing entries. If a classifier is learned directly on such data, it cannot obtain a satisfactory classification performance. In this paper, we propose an ensemble classification framework based on latent factor analysis (ECF-LFA). Its main idea includes two parts: 1) employing the latent factor analysis (LFA) to extract the latent factors (LFs) from original data, which can avoid the influence of redundant features and handle the data with many missing entries, and 2) using these extracted LFs as the input for base classifiers to conduct the ensemble learning, which can boost a base classifier’s classification accuracy. Experimental results on four benchmark datasets and three well-known classification algorithms verify that ECF-LFA can effectively improve a classifier’s performances.
{"title":"An Ensemble Classification Framework Based on Latent Factor Analysis","authors":"Xia He, Xiaoguang Lin, Di Wu, Juan Wang","doi":"10.1109/ICHMS49158.2020.9209463","DOIUrl":"https://doi.org/10.1109/ICHMS49158.2020.9209463","url":null,"abstract":"Classification, which is one of the most powerful approaches to filter valuable information from big data, is a typical supervised learning method of machine learning. In many real applications, the collected data may contain many redundant features and have some missing entries. If a classifier is learned directly on such data, it cannot obtain a satisfactory classification performance. In this paper, we propose an ensemble classification framework based on latent factor analysis (ECF-LFA). Its main idea includes two parts: 1) employing the latent factor analysis (LFA) to extract the latent factors (LFs) from original data, which can avoid the influence of redundant features and handle the data with many missing entries, and 2) using these extracted LFs as the input for base classifiers to conduct the ensemble learning, which can boost a base classifier’s classification accuracy. Experimental results on four benchmark datasets and three well-known classification algorithms verify that ECF-LFA can effectively improve a classifier’s performances.","PeriodicalId":132917,"journal":{"name":"2020 IEEE International Conference on Human-Machine Systems (ICHMS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114400656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICHMS49158.2020.9209488
E. Roth, Mirco Möncks, T. Bohné, Luisa Pumplun
The increasing demand for product customisation is leading to higher complexities within manufacturing. This imposes new challenges for the workforce. One way to support operators’ productivity may be context-aware, human-centred cyber-physical assistance systems. Human Activity Recognition (HAR) is a promising approach to enable context-awareness. However, standardised approaches to integrate HAR into existing manufacturing environments are rare. Particularly, there is a lack of available datasets of manufacturing activities. Moreover, comparative studies of inertial and visual HAR approaches are still rare. This work therefore proposes Methods-Time Measurement (MTM) as a standardised foundation for creating a manufacturing activity dataset. Subsequently, five different machine learning algorithms are tested for their recognition performance based on the dataset captured with an inertial sensor suit and an RGB-D sensor. A proof-of-concept is delivered for both sensor categories applied to the scope of 18 MTM-1 activities, whereas inertial data outperformed depth data. K-Nearest Neighbour and Bagged Tree algorithms revealed the best classification accuracy results in this context.
{"title":"Context-Aware Cyber-Physical Assistance Systems in Industrial Systems: A Human Activity Recognition Approach","authors":"E. Roth, Mirco Möncks, T. Bohné, Luisa Pumplun","doi":"10.1109/ICHMS49158.2020.9209488","DOIUrl":"https://doi.org/10.1109/ICHMS49158.2020.9209488","url":null,"abstract":"The increasing demand for product customisation is leading to higher complexities within manufacturing. This imposes new challenges for the workforce. One way to support operators’ productivity may be context-aware, human-centred cyber-physical assistance systems. Human Activity Recognition (HAR) is a promising approach to enable context-awareness. However, standardised approaches to integrate HAR into existing manufacturing environments are rare. Particularly, there is a lack of available datasets of manufacturing activities. Moreover, comparative studies of inertial and visual HAR approaches are still rare. This work therefore proposes Methods-Time Measurement (MTM) as a standardised foundation for creating a manufacturing activity dataset. Subsequently, five different machine learning algorithms are tested for their recognition performance based on the dataset captured with an inertial sensor suit and an RGB-D sensor. A proof-of-concept is delivered for both sensor categories applied to the scope of 18 MTM-1 activities, whereas inertial data outperformed depth data. K-Nearest Neighbour and Bagged Tree algorithms revealed the best classification accuracy results in this context.","PeriodicalId":132917,"journal":{"name":"2020 IEEE International Conference on Human-Machine Systems (ICHMS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116626337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICHMS49158.2020.9209502
Costanza Navarretta
This study concerns the use of speech pauses, and especially breath pauses in a Danish corpus of spontaneous dyadic conversations. Speech pauses which have specific communicative functions are investigated in relation to their occurrences before and after other communicative units, all annotated and classified in the form of dialogue acts. Breath pauses have been addressed in only few studies even though they are important in communication and therefore should be accounted for when implementing human-machine dialogue systems. Dialogue acts, on the contrary, have been one of the backbones in dialogue systems since they generalize over different expressions of common communicative functions. In the current work, we describe the annotation of dialogue acts in the corpus and present an analysis of pauses using these annotations. To our best knowledge, dialogue acts have not been previously used for analyzing the functions of breath pauses. Our analysis shows that the most common type of pause having a communicative function in the Danish conversations are breath pauses. Breath pauses in the corpus have different uses, one of these being that of delimiting speech segments which are left unfinished and are then abandoned by the speaker (retractions in dialogue acts terminology) and therefore perceivable breathing can be a useful feature for determining spoken segments which must not be included in the dialogue history in human-machine dialogue systems.
{"title":"Speech Pauses and Dialogue Acts","authors":"Costanza Navarretta","doi":"10.1109/ICHMS49158.2020.9209502","DOIUrl":"https://doi.org/10.1109/ICHMS49158.2020.9209502","url":null,"abstract":"This study concerns the use of speech pauses, and especially breath pauses in a Danish corpus of spontaneous dyadic conversations. Speech pauses which have specific communicative functions are investigated in relation to their occurrences before and after other communicative units, all annotated and classified in the form of dialogue acts. Breath pauses have been addressed in only few studies even though they are important in communication and therefore should be accounted for when implementing human-machine dialogue systems. Dialogue acts, on the contrary, have been one of the backbones in dialogue systems since they generalize over different expressions of common communicative functions. In the current work, we describe the annotation of dialogue acts in the corpus and present an analysis of pauses using these annotations. To our best knowledge, dialogue acts have not been previously used for analyzing the functions of breath pauses. Our analysis shows that the most common type of pause having a communicative function in the Danish conversations are breath pauses. Breath pauses in the corpus have different uses, one of these being that of delimiting speech segments which are left unfinished and are then abandoned by the speaker (retractions in dialogue acts terminology) and therefore perceivable breathing can be a useful feature for determining spoken segments which must not be included in the dialogue history in human-machine dialogue systems.","PeriodicalId":132917,"journal":{"name":"2020 IEEE International Conference on Human-Machine Systems (ICHMS)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123199016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICHMS49158.2020.9209426
Yoav Ben Yaakov, Joachim Meyer, Xinrun Wang, Bo An
Cyber attacks and the associated costs made cybersecurity a vital part of any system. User behavior and decisions are still a major part in the coping with these risks. We developed a model of optimal investment and human decisions with security measures, given that the effectiveness of each measure depends partly on the performance of the others. In an online experiment, participants classified events as malicious or non-malicious, based on the value of an observed variable. Prior to making the decisions, they had invested in three security measures - a firewall, an IDS or insurance. In three experimental conditions, maximal investment in only one of the measures was optimal, while in a fourth condition, participants should not have invested in any of the measures. A previous paper presents the analysis of the investment decisions. This paper reports users’ classifications of events when interacting with these systems. The use of security mechanisms helped participants gain higher scores. Participants benefited in particular from purchasing IDS and/or Cyber Insurance. Participants also showed higher sensitivity and compliance with the alerting system when they could benefit from investing in the IDS. Participants, however, did not adjust their behavior optimally to the security settings they had chosen. The results demonstrate the complex nature of risk-related behaviors and the need to consider human abilities and biases when designing cyber security systems.
{"title":"User detection of threats with different security measures","authors":"Yoav Ben Yaakov, Joachim Meyer, Xinrun Wang, Bo An","doi":"10.1109/ICHMS49158.2020.9209426","DOIUrl":"https://doi.org/10.1109/ICHMS49158.2020.9209426","url":null,"abstract":"Cyber attacks and the associated costs made cybersecurity a vital part of any system. User behavior and decisions are still a major part in the coping with these risks. We developed a model of optimal investment and human decisions with security measures, given that the effectiveness of each measure depends partly on the performance of the others. In an online experiment, participants classified events as malicious or non-malicious, based on the value of an observed variable. Prior to making the decisions, they had invested in three security measures - a firewall, an IDS or insurance. In three experimental conditions, maximal investment in only one of the measures was optimal, while in a fourth condition, participants should not have invested in any of the measures. A previous paper presents the analysis of the investment decisions. This paper reports users’ classifications of events when interacting with these systems. The use of security mechanisms helped participants gain higher scores. Participants benefited in particular from purchasing IDS and/or Cyber Insurance. Participants also showed higher sensitivity and compliance with the alerting system when they could benefit from investing in the IDS. Participants, however, did not adjust their behavior optimally to the security settings they had chosen. The results demonstrate the complex nature of risk-related behaviors and the need to consider human abilities and biases when designing cyber security systems.","PeriodicalId":132917,"journal":{"name":"2020 IEEE International Conference on Human-Machine Systems (ICHMS)","volume":"53 18","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113981565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICHMS49158.2020.9209381
Xiaoshi Chen, Li Gong, Lirong Zheng, Z. Zou
This paper proposes a human machine interaction system in the field of stroke rehabilitation, based on the concept of mirror therapy (MT). It aims to improve the hand motor function of stroke patients, enabling a true synchronization between the affected hand and non-affected hand (healthy hand) for the stroke patient. It consists of a soft exoskeleton glove, a surface electromyography (sEMG) signal collecting armband and machine learning (ML) algorithms. The glove is developed by integrating low-power motors to provide force strength for the hand movement. Unlike the rigid exoskeleton devices, the glove is comfortable to wear and lightweight, so it is more suitable for rehabilitation training of stroke patients in daily life. The armband collects the sEMG signals for pattern recognition by the ML algorithms. In the experiment, four subjects perform 10 hand gestures to collect data for model training. A comparison of data preprocessing is conducted to find the optimal data segmentation method and feature vector sets. A series of pattern recognition algorithms are developed and assessed in different aspects, including prediction accuracy, training time and predicting time. All 10 gestures can be recognized in offline mode with an accuracy up to 99.4%. The control of soft exoskeleton glove in real-time manner is also carried out, and the accuracy is 82.2%. The experiment result demonstrates the feasibility of the proposed system. The innovations and limitations of the work are discussed at the end of the paper.
{"title":"Soft Exoskeleton Glove for Hand Assistance Based on Human-machine Interaction and Machine Learning","authors":"Xiaoshi Chen, Li Gong, Lirong Zheng, Z. Zou","doi":"10.1109/ICHMS49158.2020.9209381","DOIUrl":"https://doi.org/10.1109/ICHMS49158.2020.9209381","url":null,"abstract":"This paper proposes a human machine interaction system in the field of stroke rehabilitation, based on the concept of mirror therapy (MT). It aims to improve the hand motor function of stroke patients, enabling a true synchronization between the affected hand and non-affected hand (healthy hand) for the stroke patient. It consists of a soft exoskeleton glove, a surface electromyography (sEMG) signal collecting armband and machine learning (ML) algorithms. The glove is developed by integrating low-power motors to provide force strength for the hand movement. Unlike the rigid exoskeleton devices, the glove is comfortable to wear and lightweight, so it is more suitable for rehabilitation training of stroke patients in daily life. The armband collects the sEMG signals for pattern recognition by the ML algorithms. In the experiment, four subjects perform 10 hand gestures to collect data for model training. A comparison of data preprocessing is conducted to find the optimal data segmentation method and feature vector sets. A series of pattern recognition algorithms are developed and assessed in different aspects, including prediction accuracy, training time and predicting time. All 10 gestures can be recognized in offline mode with an accuracy up to 99.4%. The control of soft exoskeleton glove in real-time manner is also carried out, and the accuracy is 82.2%. The experiment result demonstrates the feasibility of the proposed system. The innovations and limitations of the work are discussed at the end of the paper.","PeriodicalId":132917,"journal":{"name":"2020 IEEE International Conference on Human-Machine Systems (ICHMS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126503579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICHMS49158.2020.9209554
Giulia Pompili, T. L. Baldi, Davide Barcelli, D. Prattichizzo
The thumb plays an important role in grasping or pinching activities. After an injury, it requires a delicate rehabilitation program with a periodic presence of a specialist. Providing a home exercise program to patients is a fundamental aspect of rehabilitation. Home-based exercise program usually does not involve technological aids. In this paper, we propose a novel device that will augment rehabilitative outcomes, reducing costs, rehabilitation time, and providing opportunities for home rehabilitation with better patient compliance. The proposed system consists of an instrumented glove with a companion mobile-device application. The physical design of the glove is inspired by the Kapandji test, that we adapted positioning 14 patches on fingers and palm. A signal is sent to the Android application when a contact between the thumb and one of the other patches occurs. The system implements three different functionalities: i) thumb mobility assessment, ii) rehabilitation games, iii) in-game performance monitoring and results storage. The interface provides patients with on line information on actual performance and allows to monitor the activities by means of a smartphone. We administered two questionnaires to 15 healthy volunteers to 15 physical therapists for a qualitative analysis of our device. The overall emerging opinion about the device is remarkably positive.
{"title":"Development of a Low-cost Glove for Thumb Rehabilitation: Design and Evaluation","authors":"Giulia Pompili, T. L. Baldi, Davide Barcelli, D. Prattichizzo","doi":"10.1109/ICHMS49158.2020.9209554","DOIUrl":"https://doi.org/10.1109/ICHMS49158.2020.9209554","url":null,"abstract":"The thumb plays an important role in grasping or pinching activities. After an injury, it requires a delicate rehabilitation program with a periodic presence of a specialist. Providing a home exercise program to patients is a fundamental aspect of rehabilitation. Home-based exercise program usually does not involve technological aids. In this paper, we propose a novel device that will augment rehabilitative outcomes, reducing costs, rehabilitation time, and providing opportunities for home rehabilitation with better patient compliance. The proposed system consists of an instrumented glove with a companion mobile-device application. The physical design of the glove is inspired by the Kapandji test, that we adapted positioning 14 patches on fingers and palm. A signal is sent to the Android application when a contact between the thumb and one of the other patches occurs. The system implements three different functionalities: i) thumb mobility assessment, ii) rehabilitation games, iii) in-game performance monitoring and results storage. The interface provides patients with on line information on actual performance and allows to monitor the activities by means of a smartphone. We administered two questionnaires to 15 healthy volunteers to 15 physical therapists for a qualitative analysis of our device. The overall emerging opinion about the device is remarkably positive.","PeriodicalId":132917,"journal":{"name":"2020 IEEE International Conference on Human-Machine Systems (ICHMS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126530676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICHMS49158.2020.9209413
A. Economides, Chiara Baiano, Isa Zappullo, M. Conson, Joulietta Kalli-Laouri, Y. Laouris, A. Esposito
Facial expressions are important in decoding meaning and communicating information. Participants were fifty-eight Cypriot and Italian children between 6 and 11 years of age. Comparisons were made between the clinical group, composed of children with ADHD, ASD and learning disorder and the control group, composed of typically developing children. The six primary emotional facial expressions were investigated which were portrayed by contemporary faces of children and adults of both genders. There was a significant main effect for group and a significant main effect for emotion, with happiness being the most accurately decoded emotion followed by anger, surprise, sadness, disgust and fear. Significant interactions were found involving the type of stimuli, emotions and participants’ group. The results of the study are discussed considering past research and future directions.
{"title":"Is Autism, Attention Deficit Hyperactivity Disorder (ADHD) and Specific Learning Disorder linked to Impaired Emotion Recognition in Primary School Aged Children?","authors":"A. Economides, Chiara Baiano, Isa Zappullo, M. Conson, Joulietta Kalli-Laouri, Y. Laouris, A. Esposito","doi":"10.1109/ICHMS49158.2020.9209413","DOIUrl":"https://doi.org/10.1109/ICHMS49158.2020.9209413","url":null,"abstract":"Facial expressions are important in decoding meaning and communicating information. Participants were fifty-eight Cypriot and Italian children between 6 and 11 years of age. Comparisons were made between the clinical group, composed of children with ADHD, ASD and learning disorder and the control group, composed of typically developing children. The six primary emotional facial expressions were investigated which were portrayed by contemporary faces of children and adults of both genders. There was a significant main effect for group and a significant main effect for emotion, with happiness being the most accurately decoded emotion followed by anger, surprise, sadness, disgust and fear. Significant interactions were found involving the type of stimuli, emotions and participants’ group. The results of the study are discussed considering past research and future directions.","PeriodicalId":132917,"journal":{"name":"2020 IEEE International Conference on Human-Machine Systems (ICHMS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115797717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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