scholarly journals Activity Recognition Using Wearable Physiological Measurements: Selection of Features from a Comprehensive Literature Study

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5524 ◽  
Author(s):  
Inma Mohino-Herranz ◽  
Roberto Gil-Pita ◽  
Manuel Rosa-Zurera ◽  
Fernando Seoane
Keyword(s):  
Activity Recognition ◽  
Error Probability ◽  
Electrodermal Activity ◽  
Research Field ◽  
Window Length ◽  
Literature Study ◽  
Physiological Signal ◽  
Physiological Signal Processing ◽  
Electrical Bioimpedance ◽  
Health Care Applications

Activity and emotion recognition based on physiological signal processing in health care applications is a relevant research field, with promising future and relevant applications, such as health at work or preventive care. This paper carries out a deep analysis of features proposed to extract information from the electrocardiogram, thoracic electrical bioimpedance, and electrodermal activity signals. The activities analyzed are: neutral, emotional, mental and physical. A total number of 533 features are tested for activity recognition, performing a comprehensive study taking into consideration the prediction accuracy, feature calculation, window length, and type of classifier. Feature selection to know the most relevant features from the complete set is implemented using a genetic algorithm, with a different number of features. This study has allowed us to determine the best number of features to obtain a good error probability avoiding over-fitting, and the best subset of features among those proposed in the literature. The lowest error probability that is obtained is 22.2%, with 40 features, a least squares error classifier, and 40 s window length.

Learning from intelligent conversation

IMP Journal ◽  
2016 ◽  
Vol 10 (3) ◽  
pp. 512-539 ◽  
Author(s):  
Luitzen De Boer ◽  
Poul Houman Andersen
Keyword(s):  
System Theory ◽  
Design Methodology ◽  
Historical Analysis ◽  
Research Field ◽  
Literature Study ◽  
Content Type ◽  
Narrative Literature ◽  
The Relationship ◽  
Conceptual Research

Purpose The purpose of the paper is to contribute to further advancing of IMP as a research field by setting up and starting a theoretical conversation between system theory and the IMP. Design/methodology/approach The approach is based on a narrative literature study and conceptual research. Findings The authors find that system theory and cybernetics can be regarded as important sources of inspiration for early IMP research. The authors identify three specific theoretical “puzzles” in system theory that may serve as useful topics for discussion between system theorists and IMP researchers. Originality/value Only a handful of papers have touched upon the relationship between system theory and IMP before. This paper combines a narrative, historical analysis of this relationship with developing specific suggestions for using system theory as a vehicle for further advancement of IMP research.

scholarly journals Human Activity Recognition with Deep Learning: Overview, Challenges & Possibilities

2021 ◽  
Author(s):  
Pranjal Kumar
Keyword(s):  
Deep Learning ◽  
Activity Recognition ◽  
Human Activity ◽  
Well Being ◽  
Human Activity Recognition ◽  
Research Field ◽  
Daily Lives ◽  
Video Cameras ◽  
Advantages And Disadvantages

Human Activity Recognition (HAR) has become a vibrant research field over the last decade, especially because of the spread of electronic devices like mobile phones, smart cell phones, and video cameras in our daily lives. In addition, the progress of deep learning and other algorithms has made it possible for researchers to use HAR in many fields including sports, health, and well-being. HAR is, for example, one of the most promising resources for helping older people with the support of their cognitive and physical function through day-to-day activities. This study focuses on the key role machine learning plays in the development of HAR applications. While numerous HAR surveys and review articles have previously been carried out, the main/overall HAR issue was not taken into account, and these studies concentrate only on specific HAR topics. A detailed review paper covering major HAR topics is therefore essential. This study analyses the most up-to-date studies on HAR in recent years and provides a classification of HAR methodology and demonstrates advantages and disadvantages for each group of methods. This paper finally addresses many problems in the current HAR subject and provides recommendations for potential study.

scholarly journals ЕЛЕМЕНТИ ІНТЕРФЕЙСУ НАУКОВО-ДОСЛІДНОГО WEB-РЕСУРСУ PHYSIONET ТА ІМПОРТ ДАНИХ У СИСТЕМУ КОМП'ЮТЕРНОЇ МАТЕМАТИКИ MAPLE 17

2015 ◽  
Author(s):  
G. P. Chuiko ◽  
I. O. Shyian ◽  
D. A. Galyak
Keyword(s):  
Free Access ◽  
Digital Signals ◽  
Interface Elements ◽  
Medical Databases ◽  
Physiological Signal ◽  
Web Resource ◽  
Interactive Display ◽  
Physiological Signal Processing ◽  
Data Files ◽  
User Friendly

Since 1999, PhysioNet (http://physionet.org/) has offered free access via the web to large collections of recorded physiologic signals and medical databases as well as associated open-source software. The intention of this scientific resource is to stimulate current research and new investigations in the study of cardiovascular and other complex biomedical signals. PhysioBank archives include today the records obtained from healthy individuals and from patients with different diagnoses obtained under various conditions. It includes sudden cardiac death, congestive heart failure, neurological disorders, epilepsy and many others. Software packages PhysioToolkit is valuable for physiological signal processing and analysis, for creation of new databases, the interactive display and characterization of signals, the simulation of physiological and other signals. Nonetheless, a researcher should have skills to work with the operating system Unix and be knowledgeable in special commands to successful use software PhysioToolkit. Therefore, it makes sense to convert the necessary signals to a user-friendly computer algebra system. This paper describes interface elements of scientific web-resource PhysioNet, the simple methods of converting from binary medical data files to the text format and import of received digital signals into computer mathematics system Maple 17.

scholarly journals Design of User-Customized Negative Emotion Classifier Based on Feature Selection Using Physiological Signal Sensors

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4253 ◽  
Author(s):  
JeeEun Lee ◽  
Sun K. Yoo
Keyword(s):  
Feature Selection ◽  
Negative Emotion ◽  
Electrodermal Activity ◽  
Cognitive Status ◽  
Physiological Signals ◽  
Self Assessment ◽  
Physiological Signal ◽  
Distribution Shape ◽  
The Difference ◽  
The Individual

First, the Likert scale and self-assessment manikin are used to provide emotion analogies, but they have limits for reflecting subjective factors. To solve this problem, we use physiological signals that show objective responses from cognitive status. The physiological signals used are electrocardiogram, skin temperature, and electrodermal activity (EDA). Second, the degree of emotion felt, and the related physiological signals, vary according to the individual. KLD calculates the difference in probability distribution shape patterns between two classes. Therefore, it is possible to analyze the relationship between physiological signals and emotion. As the result, features from EDA are important for distinguishing negative emotion in all subjects. In addition, the proposed feature selection algorithm showed an average accuracy of 92.5% and made it possible to improve the accuracy of negative emotion recognition.

scholarly journals Evaluating physiological signal salience for estimating metabolic energy cost from wearable sensors

2019 ◽  
Vol 126 (3) ◽  
pp. 717-729 ◽  
Author(s):  
Kimberly A. Ingraham ◽  
Daniel P. Ferris ◽  
C. David Remy
Keyword(s):  
Heart Rate ◽  
Steady State ◽  
Indirect Calorimetry ◽  
Energy Cost ◽  
Electrodermal Activity ◽  
Wearable Sensors ◽  
Metabolic Energy ◽  
Physiological Signals ◽  
Physiological Signal ◽  
Signal Salience

Body-in-the-loop optimization algorithms have the capability to automatically tune the parameters of robotic prostheses and exoskeletons to minimize the metabolic energy expenditure of the user. However, current body-in-the-loop algorithms rely on indirect calorimetry to obtain measurements of energy cost, which are noisy, sparsely sampled, time-delayed, and require wearing a respiratory mask. To improve these algorithms, the goal of this work is to predict a user’s steady-state energy cost quickly and accurately using physiological signals obtained from portable, wearable sensors. In this paper, we quantified physiological signal salience to discover which signals, or groups of signals, have the best predictive capability when estimating metabolic energy cost. We collected data from 10 healthy individuals performing 6 activities (walking, incline walking, backward walking, running, cycling, and stair climbing) at various speeds or intensities. Subjects wore a suite of physiological sensors that measured breath frequency and volume, limb accelerations, lower limb EMG, heart rate, electrodermal activity, skin temperature, and oxygen saturation; indirect calorimetry was used to establish the ‘ground truth’ energy cost for each activity. Evaluating Pearson’s correlation coefficients and single and multiple linear regression models with cross validation (leave-one- subject-out and leave-one- task-out), we found that 1) filtering the accelerations and EMG signals improved their predictive power, 2) global signals (e.g., heart rate, electrodermal activity) were more sensitive to unknown subjects than tasks, while local signals (e.g., accelerations) were more sensitive to unknown tasks than subjects, and 3) good predictive performance was obtained combining a small number of signals (4–5) from multiple sensor modalities. NEW & NOTEWORTHY In this paper, we systematically compare a large set of physiological signals collected from portable sensors and determine which sensor signals contain the most salient information for predicting steady-state metabolic energy cost, robust to unknown subjects or tasks. This information, together with the comprehensive data set that is published in conjunction with this paper, will enable researchers and clinicians across many fields to develop novel algorithms to predict energy cost from wearable sensors.

scholarly journals Hardware for Recognition of Human Activities: A Review of Smart Home and AAL Related Technologies

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4227 ◽  
Author(s):  
Andres Sanchez-Comas ◽  
Kåre Synnes ◽  
Josef Hallberg
Keyword(s):  
Activity Recognition ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Fall Detection ◽  
Research Field ◽  
Health Security ◽  
Assistive Robots ◽  
Road Map ◽  
The People

Activity recognition (AR) from an applied perspective of ambient assisted living (AAL) and smart homes (SH) has become a subject of great interest. Promising a better quality of life, AR applied in contexts such as health, security, and energy consumption can lead to solutions capable of reaching even the people most in need. This study was strongly motivated because levels of development, deployment, and technology of AR solutions transferred to society and industry are based on software development, but also depend on the hardware devices used. The current paper identifies contributions to hardware uses for activity recognition through a scientific literature review in the Web of Science (WoS) database. This work found four dominant groups of technologies used for AR in SH and AAL—smartphones, wearables, video, and electronic components—and two emerging technologies: Wi-Fi and assistive robots. Many of these technologies overlap across many research works. Through bibliometric networks analysis, the present review identified some gaps and new potential combinations of technologies for advances in this emerging worldwide field and their uses. The review also relates the use of these six technologies in health conditions, health care, emotion recognition, occupancy, mobility, posture recognition, localization, fall detection, and generic activity recognition applications. The above can serve as a road map that allows readers to execute approachable projects and deploy applications in different socioeconomic contexts, and the possibility to establish networks with the community involved in this topic. This analysis shows that the research field in activity recognition accepts that specific goals cannot be achieved using one single hardware technology, but can be using joint solutions, this paper shows how such technology works in this regard.

Analisis Fikih Muamalah terhadap Tukar menukar Nomor Undian Arisan

2020 ◽  
pp. 84
Author(s):  
Yohan Sah ◽  
Eva Fauziah ◽  
Panji Adam Agus Putra
Keyword(s):  
Field Research ◽  
Research Problem ◽  
Number System ◽  
Research Field ◽  
Literature Study ◽  
Funding Sources ◽  
The Social ◽  
Social Gathering ◽  
Mutual Agreement

Abstaract. Arisan with lottery number system is a type of arisan that uses the draw method to determine the winner of the arisan and agrees on the basis of the lottery that comes out by mutual agreement. However, the fulfillment of needs that must be met immediately makes some people try to get funding sources quickly, and of course in ways that are easier to go. The practice of exchanging arisan lottery numbers by PKK Kelurahan Cikawao Village is one way to be able to meet their needs. This study aims to determine the practice of exchanging arisan lottery numbers in Cikawao Village and to know the muamalah fiqh review of arisan lottery exchange numbers. This type of research is field research (field reseach) which is a type of research by collecting data at the place of the research problem. In this study using the method of observation, interviews, and literature study. After it is collected, processed and analyzed so that a conclusion can be drawn. From the results of research the practice of exchanging the social gathering numbers in terms of the contract is not justified based on the review of muamalah fiqh, because in the practice of exchanging, there is an agreement on overpayment at the time of the contract and this is called the practice of usury, so the practice of swapping lottery numbers This social gathering is forbidden / canceled.Keywords: Arisan, qard, Buy and SaleAbstrak. Arisan dengan sistem nomor undian adalah suatu jenis arisan yang menggunakan metode pengundian untuk menetapkan pemenang arisan dan menyepakatinya berdasarkan undian yang keluar atas kesepakatan bersama. Akan  tetapi, adanya  pemenuhan  kebutuhan yang  harus  segera dipenuhi membuat sebagian orang berusahan untuk mendapatkan sumber dana dengan cepat, dan tentu saja dengan cara yang lebih mudah untuk ditempuh. Praktik tukar menukar nomor undian arisan oleh ibu-ibu PKK Kelurahan Cikawao inilah yang menjadi salah satu cara untuk dapat memenuhi kebutuhannya. Penelitian ini bertujuan untuk mengetahui praktik tukar menukar nomor undian arisan di Kelurahan Cikawao dan untuk mengetahui tinjauan fikih muamalah terhadap tukar menukar nomor undian arisan. Jenis penelitian ini adalah penelitian lapangan (field reseach) yaitu jenis penelitian dengan cara mengumpulkan data di tempat terjadinya permasalahan penelitian. Dalam penelitian ini menggunakan metode observasi, wawancara, dan studi pustaka. Setelah itu dikumpulkan, diolah dan dianalisis sehingga dapat ditarik suatu kesimpulan. Dari hasil penelitian Praktik tukar-menukar nomor arisan tersebut dari segi akadnya tidak dibenarkan berdasarkan tinjauan fikih muamalah, karena dalam praktik tukar-menukar tersebut, terdapat kesepakatan kelebihan pembayaran pada saat akad dan hal ini dinamakan dengan praktik riba, sehingga praktik tukar-menukar nomor undian arisan ini hukumnya haram/batal.Kata Kunci: Arisan, qard, jual beli

scholarly journals A Wearable Head Mounted Display Bio-Signals Pad System for Emotion Recognition

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 142
Author(s):  
Chunting Wan ◽  
Dongyi Chen ◽  
Zhiqi Huang ◽  
Xi Luo
Keyword(s):  
Emotion Recognition ◽  
Electrodermal Activity ◽  
Research Field ◽  
Acquisition System ◽  
Emotional States ◽  
Eeg Signal ◽  
Measuring Device ◽  
Head Mounted Display ◽  
Eyes Closed ◽  
Eyes Open

Multimodal bio-signals acquisition based on wearable devices and using virtual reality (VR) as stimulus source are promising techniques in emotion recognition research field. Numerous studies have shown that emotional states can be better evoked through Immersive Virtual Environments (IVE). The main goal of this paper is to provide researchers with a system for emotion recognition in VR environments. In this paper, we present a wearable forehead bio-signals acquisition pad which is attached to Head-Mounted Displays (HMD), termed HMD Bio Pad. This system can simultaneously record emotion-related two-channel electroencephalography (EEG), one-channel electrodermal activity (EDA), photoplethysmograph (PPG) and skin temperature (SKT) signals. In addition, we develop a human-computer interaction (HCI) interface which researchers can carry out emotion recognition research using VR HMD as stimulus presentation device. To evaluate the performance of the proposed system, we conducted different experiments to validate the multimodal bio-signals quality, respectively. To validate EEG signal, we have assessed the performance in terms of EEG eyes-blink task and eyes-open and eyes-closed task. The EEG eyes-blink task indicates that the proposed system can achieve comparable EEG signal quality in comparison to the dedicated bio-signals measuring device. The eyes-open and eyes-closed task proves that the proposed system can efficiently record alpha rhythm. Then we used signal-to-noise ratio (SNR) and Skin Conductance Reaction (SCR) signal to validate the performance for EDA acquisition system. A filtered EDA signal, with a high mean SNR of 28.52 dB, is plotted on HCI interface. Moreover, the SCR signal related to stimulus response can be correctly extracted from EDA signal. The SKT acquisition system has been validated effectively by the temperature change experiment when subjects are in unpleasant emotion. The pulse rate (PR) estimated from PPG signal achieved the low mean average absolute error (AAE), which is 1.12 beats per minute (BPM) over 8 recordings. In summary, the proposed HMD Bio Pad offers a portable, comfortable and easy-to-wear device for recording bio-signals. The proposed system could contribute to emotion recognition research in VR environments.

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