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Selecting and Describing Your Research Instruments

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Emerging researchers are often surprised to learn that instrument selection is a complex and important step in the process of research design. This concise guide explains how to identify appropriate instruments, select the best ones for the job, and properly describe the instruments so that others will know how and why they were chosen.

Each chapter in the book focuses on a specific aspect of instrument selection, with illuminating examples and helpful worksheets to fill out along the way. Part of APA's Concise Guides to Conducting Behavioral, Health, and Social Science Research series, this book is aimed at undergraduate students in research methods courses or others with a lab or research project.

Series Foreword

Acknowledgments

Introduction

  • Identifying and Defining the Constructs and Variables to Measure
  • Types of Instruments
  • Identifying Available Instruments
  • Gathering Information
  • Organizing and Taking Good Notes
  • Using the Evidence to Guide Your Selection
  • Obtaining Permission and Piloting the Instrument
  • Following Ethical Principles and Guidelines
  • Describing the Instruments Effectively for Different Audiences
  • Troubleshooting

About the Author

About the Series Editor

Kelly McClure, PhD, is associate professor and chair of psychology at La Salle University in Philadelphia, Pennsylvania. She received her doctorate from Drexel University in 2002.

She was a co-editor of Practitioners Guide to Empirically Based Measures of Depression and is currently an associate editor of Clinical Psychology: Science and Practice .

Her main research interests are in social problem solving and coping with cancer.

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EMG Based Human Machine Integration for IoT Based Instruments

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research instruments chapter 3

  • V. Rajesh   ORCID: orcid.org/0000-0001-5630-5637 12 ,
  • V. Sri Sravan 13 &
  • N. Nanda Prakash   ORCID: orcid.org/0000-0003-0771-0788 12  

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 1029))

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  • International Conference on Internet of Everything and Quantum Information Processing

Introducing the application of hand gestures in human-computer interaction, this study presents a novel approach that employs artificial neural networks (ANNs) to analyze muscle activity and distinguish hand movements from electromyograms (EMGs). The emphasis on creating a user-friendly and stress-free environment is reflected in the limitation of EMG detection to three specific muscle groups in the arm. The analysis of EMG signals yields parameters related to the temporal patterns of muscle contractions, each uniquely associated with a specific gesture. An experimental study was conducted to assess the system’s ability to accurately recognize six distinct arm movements. The results demonstrate that the algorithm achieves an impressive 98% accuracy rate in identifying all six motions. One notable advantage of this system is its ease of training and seamless real-time execution once the training process is completed.

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Department of ECE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, 522302, A.P., India

V. Rajesh & N. Nanda Prakash

Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, 522302, A.P., India

V. Sri Sravan

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Aurel Vlaicu University of Arad, Arad, Romania

Valentina E. Balas

Dept. of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India

Kolla Bhanu Prakash

Koneru Lakshmaiah Education Foundation, Vijayawada, Andhra Pradesh, India

G. P. Saradhi Varma

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Rajesh, V., Sravan, V.S., Prakash, N.N. (2024). EMG Based Human Machine Integration for IoT Based Instruments. In: E. Balas, V., Prakash, K.B., Varma, G.P.S. (eds) Proceedings of the International Conference on Internet of Everything and Quantum Information Processing. IEQIP 2023. Lecture Notes in Networks and Systems, vol 1029. Springer, Cham. https://doi.org/10.1007/978-3-031-61929-8_4

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  2. PDF Selecting and Describing Your Research Instruments

    Advisor Consultation Checklist Use the checklist below to ensure that you consulted with your advisor during the key steps in the process of selecting and describing your research instruments. 1. _____ Read this checklist. 2. _____ Made an appointment for our first meeting to discuss the instrument selection. 3.

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    CHAPTER 3 Research methodology 3.1 INTRODUCTION This chapter deals with the research methodology of the study, including the research design, setting, population, sample and data-collection instrument. 3.2 RESEARCH DESIGN Polit and Hungler (1999:155) describe the research design as a blueprint, or outline, for conducting

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    3. 3. 2 Research Instrument Research instruments are tools used in the research for obtaining relevant data to research's project and there are many alternatives from which to choose (Wilkinson & Birmingham, 2003, p. 3). The data were collected to answer research questions of the research. There were five research instruments utilized

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  11. PDF Chapter Three: Research Methodology

    3- 1. Chapter Three: Research Methodology. 3.1 Introduction. The way in which research is conducted may be conceived of in terms of the research philosophy subscribed to, the research strategy employed and so the research instruments utilised (and perhaps developed) in the pursuit of a goal - the research objective(s) - and the quest for the ...

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  13. PDF Designing a Qualitative Study

    Designing a Qualitative Study. 3. esigning a Qualitative StudyIthink metaphorically of qualitative research as an intricate fabric com- posed of minute threads, many colors, different textures, a. d various blends of material. This fabric is n. t explained easily or simply. Like the loom on which fabric is woven, general assumptions and ...

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  15. Selecting and Describing Your Research Instruments

    Each chapter in the book focuses on a specific aspect of instrument selection, with illuminating examples and helpful worksheets to fill out along the way. Part of APA's Concise Guides to Conducting Behavioral, Health, and Social Science Research series, this book is aimed at undergraduate students in research methods courses or others with a ...

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  24. EMG Based Human Machine Integration for IoT Based Instruments

    The third gesture is wrist extension (Gesture 3), which involves an outward movement of the wrist. The fourth and final gesture chosen is thumb flexion (Gesture 4), characterized by the thumb bending inward [1,2,3]. Our research findings indicate that, except for minor variations in overall amplitude, both hands produce very similar EMG waveforms.