Search results
1 – 10 of over 10000Kanokwan Srisupornkornkool, Kanphajee Sornkaew, Kittithat Chatkanjanakool, Chayanit Ampairattana, Pariyanoot Pongtasom, Sompiya Somthavil, Onuma Boonyarom, Kornanong Yuenyongchaiwat and Khajonsak Pongpanit
To compare the electromyography (EMG) features during physical and imagined standing up in healthy young adults.
Abstract
Purpose
To compare the electromyography (EMG) features during physical and imagined standing up in healthy young adults.
Design/methodology/approach
Twenty-two participants (ages ranged from 20–29 years old) were recruited to participate in this study. Electrodes were attached to the rectus femoris, biceps femoris, tibialis anterior and the medial gastrocnemius muscles of both sides to monitor the EMG features during physical and imagined standing up. The %maximal voluntary contraction (%MVC), onset and duration were calculated.
Findings
The onset and duration of each muscle of both sides had no statistically significant differences between physical and imagined standing up (p > 0.05). The %MVC of all four muscles during physical standing up was statistically significantly higher than during imagined standing up (p < 0.05) on both sides. Moreover, the tibialis anterior muscle of both sides showed a statistically significant contraction before the other muscles (p < 0.05) during physical and imagined standing up.
Originality/value
Muscles can be activated during imagined movement, and the patterns of muscle activity during physical and imagined standing up were similar. Imagined movement may be used in rehabilitation as an alternative or additional technique combined with other techniques to enhance the STS skill.
Details
Keywords
Abstract
Details
Keywords
M'hamed Bilal Abidine, Mourad Oussalah, Belkacem Fergani and Hakim Lounis
Mobile phone-based human activity recognition (HAR) consists of inferring user’s activity type from the analysis of the inertial mobile sensor data. This paper aims to mainly…
Abstract
Purpose
Mobile phone-based human activity recognition (HAR) consists of inferring user’s activity type from the analysis of the inertial mobile sensor data. This paper aims to mainly introduce a new classification approach called adaptive k-nearest neighbors (AKNN) for intelligent HAR using smartphone inertial sensors with a potential real-time implementation on smartphone platform.
Design/methodology/approach
The proposed method puts forward several modification on AKNN baseline by using kernel discriminant analysis for feature reduction and hybridizing weighted support vector machines and KNN to tackle imbalanced class data set.
Findings
Extensive experiments on a five large scale daily activity recognition data set have been performed to demonstrate the effectiveness of the method in terms of error rate, recall, precision, F1-score and computational/memory resources, with several comparison with state-of-the art methods and other hybridization modes. The results showed that the proposed method can achieve more than 50% improvement in error rate metric and up to 5.6% in F1-score. The training phase is also shown to be reduced by a factor of six compared to baseline, which provides solid assets for smartphone implementation.
Practical implications
This work builds a bridge to already growing work in machine learning related to learning with small data set. Besides, the availability of systems that are able to perform on flight activity recognition on smartphone will have a significant impact in the field of pervasive health care, supporting a variety of practical applications such as elderly care, ambient assisted living and remote monitoring.
Originality/value
The purpose of this study is to build and test an accurate offline model by using only a compact training data that can reduce the computational and memory complexity of the system. This provides grounds for developing new innovative hybridization modes in the context of daily activity recognition and smartphone-based implementation. This study demonstrates that the new AKNN is able to classify the data without any training step because it does not use any model for fitting and only uses memory resources to store the corresponding support vectors.
Details
Keywords
Jani Koskinen, Kai Kristian Kimppa, Janne Lahtiranta and Sami Hyrynsalmi
The competition in the academe has always been tough, but today, the academe seems to be more like an industry than an academic community as academics are evaluated through…
Abstract
Purpose
The competition in the academe has always been tough, but today, the academe seems to be more like an industry than an academic community as academics are evaluated through quantified and economic means.
Design/methodology/approach
This article leans on Heidegger’s thoughts on the essence of technology and his ontological view on being to show the dangers that lie in this quantification of researchers and research.
Findings
Despite the benefits that information systems (ISs) offer to people and research, it seems that technology has made it possible to objectify researchers and research. This has a negative impact on the academe and should thus be looked into especially by the IS field, which should note the problems that exist in its core. This phenomenon of quantified academics is clearly visible at academic quantification sites, where academics are evaluated using metrics that count their output. It seems that the essence of technology has disturbed the way research is valued by emphasising its quantifiable aspects. The study claims that it is important to look for other ways to evaluate researchers rather than trying to maximise research production, which has led to the flooding of articles that few have the time or interest to read.
Originality/value
This paper offers new insights into the current phenomenon of quantification of academics and underlines the need for critical changes if in order to achieve the academic culture that is desirable for future academics.
Details
Keywords
James McAlexander, Rachel Nelson and Chris Bates
Entrepreneurship is a source of innovation, job creation, and vibrancy for local and regional economies. As a direct result, there is a profound interest in creating an…
Abstract
Entrepreneurship is a source of innovation, job creation, and vibrancy for local and regional economies. As a direct result, there is a profound interest in creating an infrastructure that effectively encourages entrepreneurship and incubates entrepreneurial endeavors. Western State University has responded to this call by developing the Harvey Entrepreneurship Program, which is integrated in the Enterprise Residential College.The Harvey program provides a socially embedded experiential learning approach to entrepreneurial education. Faculty, students, entrepreneurs, and technical experts are drawn together in an environment that provides space for business incubators and an entrepreneurially focused curriculum. In this article, we present a case study in which we use qualitative research methods to explore the benefits and challenges of creating such a program.The delivery model that Enterprise Residential College provides for entrepreneurial education is examined through the perspectives of program administrators, faculty, and students. The findings reveal evidence that a residential college can form a powerful nexus of formal instruction, experiential learning, socialization, and networking to influence entrepreneurship. We discuss relevant findings that may aid others considering similar endeavors.