| Description |
1 online resource (508 p.) |
| Series |
Artificial Intelligence (AI): Elementary to Advanced Practices Series |
|
Artificial Intelligence (AI): Elementary to Advanced Practices Series
|
| Contents |
Cover -- Half Title -- Series -- Title -- Copyright -- Contents -- Preface -- Acknowledgments -- Editors -- Contributors -- Chapter 1 An Overview of AIoMT Applications -- 1.1 Introduction -- 1.1.1 Key Contributions of the Chapter -- 1.1.2 Chapter Organization -- 1.2. Related Work -- 1.2.1 Sensor Layer -- 1.2.2 Edge Layer -- 1.2.3 Server Layer -- 1.2.4 Communication -- 1.3. Applications -- 1.3.1 Continuous Health Monitoring -- 1.3.2 Healthcare-Related Prediction -- 1.3.3 E-Medical Healthcare -- 1.4. Case Study: Deep Learning-based Falling Detection for Seniors Living Alone |
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1.4.1 Related Work -- 1.4.3 MARS System-Methodology -- 1.4.4 Experimental Study -- 1.5. Challenges and Future Directions -- 1.5.1 Challenges -- 1.5.2 Future Directions -- 1.6 Conclusions -- References -- Chapter 2 Wearable Medical Electronics in Artificial Intelligence of Medical Things -- 2.1 Introduction -- 2.1.1 Key Contributions of the Chapter -- 2.1.2 Chapter Organization -- 2.2 Wearable Medical Electronics -- 2.2.1 Electronic Sensor Traits -- 2.3 Electronic Signals in Sensors -- 2.3.1 Gait Analysis -- 2.3.2 Photoplethysmography -- 2.3.3 Electromyography -- 2.3.4 Auscultation |
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2.4 Challenges of Electronic Devices in the AIoMT -- 2.4.1 Data Security Threats -- 2.4.2 Data Interoperability -- 2.4.3 Regulatory Challenges -- 2.4.4 High Infrastructure Costs -- 2.4.5 Standardization Challenges -- 2.4.6 Cybersecurity -- 2.4.7 Device Mobility -- 2.4.8 Adoption Scale -- 2.4.9 Advanced Analytics -- 2.4.10 Trust Maintenance -- 2.4.11 Data Security -- 2.4.12 Licensing Challenge -- 2.5 Benefits of the AIoMT -- 2.5.1 Medical Diagnosis -- 2.5.2 Medical Treatment -- 2.5.3 Patient Empowerment -- 2.5.4 Reduction in Medical Costs -- 2.5.5 Reduction in Human Error |
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2.6 Challenges of AIoMTs -- 2.6.1 Privacy Concerns -- 2.6.2 Missteps and Errors -- 2.6.3 Data Management and Power Issues -- 2.6.4 Bias -- 2.7 Limitation of AIoMT -- 2.8 Future Research Direction -- 2.9 Conclusions and Future Scope -- References -- Chapter 3 Electronic Devices in the Artificial Intelligence of the Internet of Medical Things (AIoMT) -- 3.1 Introduction -- 3.1.1 Key Contributions of the Chapter -- 3.1.2 Chapter Organization -- 3.2 Electronic Sensors in the IoMT -- 3.2.1 Electronic Sensor Traits -- 3.3 Electronic Signals -- 3.3.1 Gait Analysis -- 3.3.2 Photoplethysmography |
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3.3.3 Electromyography -- 3.3.4 Auscultation -- 3.4 Challenges of Electronic Devices in the AIoMT -- 3.4.1 Data Security Threats -- 3.4.2 Data Interoperability -- 3.4.3 Regulatory Challenges -- 3.4.4 High Infrastructure Costs -- 3.4.5 Standardization Challenges -- 3.4.6 Cybersecurity -- 3.4.7 Device Mobility -- 3.4.8 Adoption Scale -- 3.4.9 Advanced Analytics -- 3.4.10 Trust Maintenance -- 3.4.11 Data Security -- 3.4.12 Licensing Challenge -- 3.5 Benefits of the AIoMT Reviewed -- 3.5.1 Medical Diagnosis -- 3.5.2 Medical Treatment -- 3.5.3 Patient Empowerment -- 3.5.4 Reduction in Medical Costs |
| Summary |
The fast-growing number of patients suffering from various ailments has overstretched the carrying capacity of traditional healthcare systems. This handbook addresses the increased need to tackle security issues and preserve patients' privacy concerns in AIoMT devices and systems |
| Notes |
Description based upon print version of record |
|
3.5.5 Reduction in Human Errors |
| Form |
Electronic book
|
| Author |
Balas, Valentina Emilia
|
|
Solanki, Vijender Kumar
|
|
Lee, Cheng-Chi
|
|
Obaidat, Mohammad S
|
| ISBN |
9781000963267 |
|
1000963268 |
|
