Communication Through Haptics During Human Collaborative Manipulation

2018 ◽  
Vol 15 (03) ◽  
pp. 1850003
Author(s):  
Maria Javaid
Keyword(s):  
Activities Of Daily Living ◽  
Daily Living ◽  
User Study ◽  
Decision Rules ◽  
Elderly Person ◽  
Machine Learning Techniques ◽  
Communication Interface ◽  
Assistive Robot ◽  
Haptic Communication ◽  
User Friendly

This paper describes research towards understanding haptic communication during planar object manipulation. In particular, a classification algorithm that classifies four stages of manipulation of a planar object is described. This research was performed as a part of a broader research project which has the goal of developing a user-friendly communication interface for an elderly-assistive robot. The manipulation of planar object was studied in detail as it happened very frequently during user study involving a caregiver helping an elderly person with the activities of daily living. For observing human haptic interaction, a sensory glove was developed. Further data collection was conducted in the laboratory setting and data was analyzed using various machine learning techniques. Based on this analysis, decision rules were derived that give insight into human-to-human collaborative manipulation of planar objects and successfully identified several classes of manipulative actions. The developed decision tree-based algorithm was then tested on the data of a user study that involved a caregiver assisting an elderly person in the activities of daily living. The developed algorithm also successfully classifies manipulation actions in real-time. This information is particularly interesting as it does not depend on any particular sensor and thus can be used by other researchers to further study haptic communication.

scholarly journals Eye-Gaze Control of a Wheelchair Mounted 6DOF Assistive Robot for Activities of Daily Living

2021 ◽  
Author(s):  
Md Samiul Haque Sunny ◽  
Md Ishrak Islam Zarif ◽  
Ivan Rulik ◽  
Javier Sanjuan ◽  
Mohammad Habibur Rahman ◽  
...  
Keyword(s):  
User Interface ◽  
Activities Of Daily Living ◽  
Graphical User Interface ◽  
Daily Living ◽  
User Study ◽  
Eye Gaze ◽  
People With Disabilities ◽  
Control Architecture ◽  
Assistive Robot ◽  
Healthy Participants

Abstract Background: Building control architecture that balances the assistive manipulation systems with the benefits of direct human control is a crucial challenge of human-robot collaboration. It promises to help people with disabilities more efficiently control wheelchair and wheelchair-mounted robot arms to accomplish activities of daily living.Methods: In this paper, our research objective is to design an eye-tracking assistive robot control system capable of providing targeted engagement and motivating individuals with a disability to use the developed method for self-assistance activities of daily living. The graphical user interface is designed and integrated with the developed control architecture to achieve the goal.Results: We evaluated the system by conducting a user study. Ten healthy participants performed five trials of three manipulation tasks using the graphical user interface and the developed control framework. The 100% success rate on task performance demonstrates the effectiveness of our system for individuals with motor impairments to control wheelchair and wheelchair-mounted assistive robotic manipulators.Conclusions: We demonstrated the usability of using this eye-gaze system to control robotic arm mounted on wheelchair in activities of daily living for the people with disabilities. We found high levels of acceptance with higher ratings in evaluation of the system with healthy participants. Trial registration: Not applicable.

scholarly journals Eye-gaze control of a wheelchair mounted 6DOF assistive robot for activities of daily living

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Md Samiul Haque Sunny ◽  
Md Ishrak Islam Zarif ◽  
Ivan Rulik ◽  
Javier Sanjuan ◽  
Mohammad Habibur Rahman ◽  
...  
Keyword(s):  
User Interface ◽  
Activities Of Daily Living ◽  
Graphical User Interface ◽  
Daily Living ◽  
User Study ◽  
Eye Gaze ◽  
People With Disabilities ◽  
Control Architecture ◽  
Assistive Robot ◽  
Healthy Participants

Abstract Background Building control architecture that balances the assistive manipulation systems with the benefits of direct human control is a crucial challenge of human–robot collaboration. It promises to help people with disabilities more efficiently control wheelchair and wheelchair-mounted robot arms to accomplish activities of daily living. Methods In this study, our research objective is to design an eye-tracking assistive robot control system capable of providing targeted engagement and motivating individuals with a disability to use the developed method for self-assistance activities of daily living. The graphical user interface is designed and integrated with the developed control architecture to achieve the goal. Results We evaluated the system by conducting a user study. Ten healthy participants performed five trials of three manipulation tasks using the graphical user interface and the developed control framework. The 100% success rate on task performance demonstrates the effectiveness of our system for individuals with motor impairments to control wheelchair and wheelchair-mounted assistive robotic manipulators. Conclusions We demonstrated the usability of using this eye-gaze system to control a robotic arm mounted on a wheelchair in activities of daily living for people with disabilities. We found high levels of acceptance with higher ratings in the evaluation of the system with healthy participants.

scholarly journals Automated Classification of Normal Control and Early-Stage Dementia Based on Activities of Daily Living (ADL) Data Acquired from Smart Home Environment

2021 ◽  
Vol 18 (24) ◽  
pp. 13235
Author(s):  
Lee-Nam Kwon ◽  
Dong-Hun Yang ◽  
Myung-Gwon Hwang ◽  
Soo-Jin Lim ◽  
Young-Kuk Kim ◽  
...  
Keyword(s):  
Activities Of Daily Living ◽  
Normal Control ◽  
Daily Living ◽  
Smart Home ◽  
Early Stage ◽  
Machine Learning Techniques ◽  
Evaluation Tool ◽  
Dementia Patients ◽  
Diagnosis Of Dementia

With the global trend toward an aging population, the increasing number of dementia patients and elderly living alone has emerged as a serious social issue in South Korea. The assessment of activities of daily living (ADL) is essential for diagnosing dementia. However, since the assessment is based on the ADL questionnaire, it relies on subjective judgment and lacks objectivity. Seven healthy seniors and six with early-stage dementia participated in the study to obtain ADL data. The derived ADL features were generated by smart home sensors. Statistical methods and machine learning techniques were employed to develop a model for auto-classifying the normal controls and early-stage dementia patients. The proposed approach verified the developed model as an objective ADL evaluation tool for the diagnosis of dementia. A random forest algorithm was used to compare a personalized model and a non-personalized model. The comparison result verified that the accuracy (91.20%) of the personalized model was higher than that (84.54%) of the non-personalized model. This indicates that the cognitive ability-based personalization showed encouraging performance in the classification of normal control and early-stage dementia and it is expected that the findings of this study will serve as important basic data for the objective diagnosis of dementia.

scholarly journals Classification of Activities of Daily living using Smart Phones

2019 ◽  
Vol 8 (3) ◽  
pp. 2984-2988
Keyword(s):  
Activities Of Daily Living ◽  
Daily Living ◽  
Human Life ◽  
Smart Phone ◽  
Smart Phones ◽  
Machine Learning Techniques ◽  
Accelerometer Sensor ◽  
Learning Techniques ◽  
Direct Input

Smart phones have become an integral part of everyday human life. These phones are packed with various sensors for different purposes. Most of them are used for understanding the environment in which the user uses the phone so that the device could respond rapidly. Indirectly the phone extracts context information of the users like the activity performed using accelerometer and gyroscope sensors. This information can be used for a variety of applications like home automation, smart environment, etc to perform automatic changes to the environment without direct input from the user. This paper deals with the classification of activities of daily living like walking, jogging, sitting, standing, upstairs and downstairs using the data collected from accelerometer sensor within the smart phone. A comparative analysis has been performed on different machine learning techniques for activity classification.

Development of Power Assist Wear Using Pneumatic Rubber Artificial Muscles

2009 ◽  
Vol 21 (5) ◽  
pp. 607-613 ◽  
Author(s):  
Toshiro Noritsugu ◽  
◽  
Masahiro Takaiwa ◽  
Daisuke Sasaki
Keyword(s):  
Activities Of Daily Living ◽  
Daily Living ◽  
Artificial Muscle ◽  
Innovative Technology ◽  
Artificial Muscles ◽  
Disabled People ◽  
Assist Device ◽  
Assist Devices ◽  
Heavy Work ◽  
User Friendly

In the future, when the average age of the members of society becomes advanced, an innovative technology to assist the activities of daily living of elderly and disabled people and to assist in the heavy work in nursing will be desired. To develop such a technology, an actuator that is safe and user-friendly is required. It should be small, lightweight, and sufficiently soft. Such an actuator is available in artificial muscle made of pneumatic rubber. We have developed some types of pneumatic rubber artificial muscles and applied them to wearable power assist devices. A wearable power assist device is fitted to the human body to assist the power of muscles that support the activities of daily living, rehabilitation, training, and so on. In this paper, some types of pneumatic rubber artificial muscles developed and manufactured in our laboratory are presented. Furthermore, two kinds of wearable power assist devices driven by the rubber artificial muscles are described. Finally, some evaluations clarify the effectiveness of pneumatic rubber artificial muscle for innovative human assistance technologies.

scholarly journals OS3.3 Development of an EORTC questionnaire measuring instrumental activities of daily living (IADL) in patients with brain tumours: phase I-III

2019 ◽  
Vol 21 (Supplement_3) ◽  
pp. iii9-iii9
Author(s):  
Q Oort ◽  
L Dirven ◽  
F Boele ◽  
R Grant ◽  
H Sato ◽  
...  
Keyword(s):  
Activities Of Daily Living ◽  
Phase I ◽  
Brain Tumour ◽  
Phase Ii ◽  
Daily Living ◽  
Decision Rules ◽  
Questionnaire Development ◽  
Field Testing ◽  
Phase Iii ◽  
Item List

Abstract BACKGROUND In brain tumour patients, impairments in every day functioning can impact quality of life, and are therefore an important outcome in both clinical trials and practice. One way to measure every day functioning is with an activities of daily living (ADL) questionnaire. Instrumental ADL (IADL) are the cognitively more complex activities, that are essential to function autonomously within society. Cognitive decline may therefore negatively impact IADL, making these activities particularly relevant to brain tumour patients. The aim of this study is to develop a reliable and valid questionnaire to measure IADL in primary malignant and metastatic brain tumour patients. MATERIAL AND METHODS The questionnaire development study followed the standard European Organisation for Research and Treatment of Cancer (EORTC) four phase methodology: (I) generation of activities list, (II) construction of item list, (III) pre-testing, and (IV) field testing. This report covers phases I-III. To ensure cross-cultural validity, participants were recruited from different countries (The Netherlands, United Kingdom, Italy, Austria and Japan). In phase I, potential activities were identified based on a literature review and in-depth interviews with patients, proxies and healthcare professionals. In phase II, activities were turned into items, and translated into all required languages by the EORTC Translation Unit. In phase III, the item list was pre-tested in patient-proxy dyads. In accordance with predetermined decision rules to reduce items, final items were selected, and preliminary psychometric properties (i.e. factor structure, validity, reliability) were assessed. RESULTS Phase I (N=44 dyads) resulted in 59 IADL activities which were converted into 59 items in phase II. In phase III, N=85 dyads completed and reviewed this item list. The item list was subsequently reduced to 32 items. An exploratory factor analysis indicated several items measuring similar underlying constructs (e.g. domestic life and using computer/smartphone) showing acceptable to good (α≥0.7) internal consistency (range α=0.69–0.89). Seven items were less related to these underlying constructs (e.g. work or managing your own medication), and therefore single items. Construct validity, measured with known-group comparisons analyses between cognitively impaired and unimpaired patients, showed significant differences in scores between the two groups on some scales and several single items. CONCLUSION The currently developed EORTC IADL-BN32 questionnaire can be a valuable asset in assessing IADL functioning in brain tumour patients, but further validation in phase IV is required and is planned.

A useful development in measuring activities of daily living

2015 ◽  
Vol 27 (9) ◽  
pp. 1417-1417
Author(s):  
David Ames
Keyword(s):  
Activities Of Daily Living ◽  
Cognitive Aging ◽  
Daily Living ◽  
Editorial Team ◽  
Amyloid Pet ◽  
Prodromal Ad ◽  
Prodromal Alzheimer’S Disease ◽  
1960S And 1970S ◽  
The 1960S ◽  
User Friendly

Standard activities of daily living (ADL) scales developed in the 1960s and 1970s do not capture the subtle impairments seen in individuals with progressive mild cognitive impairment (MCI), which in many cases is due to prodromal Alzheimer's disease (AD). Given the promise of treatments now in development to modify the underlying AD process, early detection of MCI may become very important in future. De Vriendt and colleagues, whose paper has been chosen by the editorial team of International Psychogeriatrics, to be paper of the month in this issue, are to be congratulated for developing and validating the advanced ADL tool with the aim of providing a useful ADL measure to distinguish normal from pathological cognitive aging. They have assessed a large sample (150 people with AD, MCI and healthy controls) and report acceptable parameters for discrimination of these three groups using the instrument they have developed. The next step will be to try it out in a variety of clinical populations, settings, and cultures and perhaps to see how well it stacks up against other methods of detecting preclinical and prodromal AD (e.g. amyloid PET scans or lumbar punctures). The publication of this very good paper will allow other teams around the world to start using this user-friendly instrument and I await the outcome of further work on it with great interest.

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