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Wearable and Wireless Systems for Healthcare I : Gait and Reflex Response Quantification
| Wearable and Wireless Systems for Healthcare I : Gait and Reflex Response Quantification |
| Autore | LeMoyne Robert |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (206 pages) |
| Altri autori (Persone) | MastroianniTimothy |
| Collana | Smart Sensors, Measurement and Instrumentation Series |
| ISBN |
9789819724390
9789819724383 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- 1 Wearable and Wireless Systems for Gait Analysis and Reflex Quantification -- 1.1 Introduction -- 1.2 Summary of the Pending Chapters -- 1.3 Conclusion -- References -- 2 Traditional Clinical Evaluation of Gait and Reflex Response by Ordinal Scale -- 2.1 Introduction -- 2.2 Ordinal Scale for Quantification of Reflex Response -- 2.3 Ordinal Scale Technique for Gait -- 2.4 Ordinal Scale Strategy for Friedreich's Ataxia -- 2.5 Transition to Wearable and Wireless Systems -- 2.6 Conclusion -- References -- 3 Quantification Systems Appropriate for a Clinical Setting -- 3.1 Introduction -- 3.2 Conventional Systems for Gait Analysis -- 3.2.1 Foot Switches -- 3.2.2 Electrogoniometers -- 3.2.3 Electromyogram (EMG) -- 3.2.4 Metabolic Analysis -- 3.2.5 Optical Motion Cameras (Kinematics of Human Motion) -- 3.2.6 Force Plates -- 3.3 Synergistic Operation of Clinical Gait Laboratory Resources for Gait Analysis and Associated Signal Processing -- 3.4 Electromechanical Techniques for Reflex Quantification -- 3.5 Conclusion -- References -- 4 The Rise of Inertial Measurement Units -- 4.1 Introduction -- 4.2 Evolutionary Pathway for Inertial Sensors -- 4.3 Application Scenarios for Accelerometer Systems -- 4.4 Wireless Accelerometer Systems for Gait Analysis -- 4.5 Conclusion -- References -- 5 Portable Wearable and Wireless Systems for Gait and Reflex Response Quantification -- 5.1 Introduction -- 5.2 First Generation Wireless Reflex Quantification Device -- 5.3 Second Generation Wireless Reflex Quantification Device -- 5.4 Third Generation Wireless Quantified Reflex Device -- 5.5 Artificial Reflex System -- 5.6 Wireless Accelerometer Reflex Quantification System Characterizing Response and Latency -- 5.7 Fourth Generation Wireless Quantified Reflex Device -- 5.8 Gait Analysis Using Wearable and Wireless Accelerometer Nodes.
5.9 Virtual Proprioception -- 5.10 Further Applications of Wearable and Wireless Inertial Sensor Systems for Gait Quantification -- 5.11 Conclusion -- References -- 6 Smartphones and Portable Media Devices as Wearable and Wireless Systems for Gait and Reflex Response Quantification -- 6.1 Introduction -- 6.2 Smartphone Quantifying Gait as a Wireless Accelerometer Platform -- 6.3 Post-processing and Numerical Analysis for the Acquired Acceleration Waveform for Gait -- 6.4 Portable Media Device for Quantifying Gait as a Wireless Accelerometer Platform -- 6.5 Smartphone Wireless Accelerometer Platform for Quantification of Prosthetic Gait -- 6.6 Smartphone Wireless Gyroscope Platform for Quantification of Hemiplegic Reduced Arm Swing -- 6.7 Portable Media Device Functioning as a Wireless Gyroscope Platform for Quantification of Reduced Arm Swing for Erb's Palsy -- 6.8 Quantification of Patellar Tendon Reflex Response Through Portable Media Device and Smartphone as a Wireless Accelerometer Platform -- 6.9 Quantification of Patellar Tendon Reflex Response Through Smartphone and Portable Media Device as a Wireless Gyroscope Platform -- 6.10 Other Research Applications Regarding the Smartphone for Gait Analysis -- 6.11 Network Centric Therapy by Application of the Smartphone and Portable Media Device -- 6.12 Conclusion -- References -- 7 Bluetooth Inertial Sensors for Gait and Reflex Response Quantification with Perspectives Regarding Cloud Computing and the Internet of Things -- 7.1 Introduction -- 7.2 Utility of Bluetooth -- 7.3 Applications of Bluetooth Connected Sensors for Gait Analysis -- 7.4 Wearable and Wireless Inertial Sensors Using Bluetooth, Tablet, and Cloud Computing -- 7.5 Bluetooth Wireless Capability for Reflex Quantification -- 7.6 Relevance for Sensor Fusion -- 7.7 Internet of Things. 7.8 Network Centric Therapy: The Significance of Bluetooth -- 7.9 Conclusion -- References -- 8 Quantifying the Spatial Position Representation of Gait Through Sensor Fusion -- 8.1 Introduction -- 8.2 Sensor Level -- 8.3 Orientation Filter -- 8.3.1 Kalman Filter -- 8.3.2 Gradient Descent Orientation Filter -- 8.4 Quaternions -- 8.5 Zero Velocity Update -- 8.6 Velocity Estimation and Trajectory Formation -- 8.7 Network Centric Therapy and the Role of Sensor Fusion -- 8.8 Conclusion -- References -- 9 Role of Machine Learning for Gait and Reflex Response Classification -- 9.1 Introduction -- 9.2 Waikato Environment for Knowledge Analysis (WEKA) for Machine Learning Classification of Human Movement Characteristics Through Wearable and Wireless Devices -- 9.2.1 J48 Decision Tree -- 9.2.2 K-nearest Neighbors -- 9.2.3 Logistic Regression -- 9.2.4 Support Vector Machine -- 9.2.5 Multilayer Perceptron Neural Network -- 9.2.6 Attribute-Relation File Format (ARFF) File -- 9.3 Utility of Machine Learning with Future Perspective on Network Centric Therapy -- 9.4 Conclusion -- References -- 10 Homebound Therapy with Wearable and Wireless Systems -- 10.1 Introduction -- 10.2 Portable Media Device Wireless Accelerometer Platform for Assistive Device Usage Evaluation -- 10.3 Smartphone Wireless Gyroscope Platform for Ankle Rehabilitation -- 10.4 Portable Media Device Wireless Gyroscope Platform for a Wobble Board -- 10.5 Virtual Proprioception for Eccentric Training -- 10.6 Network Centric Therapy for Homebound Therapy with Wearable and Wireless Systems -- 10.7 Conclusion -- References -- 11 Future Perspective of Network Centric Therapy -- 12 Evolutions for Wearable and Wireless Systems -- 12.1 Introduction -- 12.2 Conformal Wearables and Wireless Inertial Sensor Systems -- 12.3 Miniaturized Wearable and Wireless Inertial Sensor Systems. 12.4 Context for the Appropriate Selection of a Wearable and Wireless System -- 12.5 Domains for Wearable and Wireless Systems for Healthcare: Gait Analysis, Homebound Therapy, and Quantifiable Exercise -- 12.6 Conclusion -- References -- 13 Gait Analysis with Advanced Wearable and Wireless Systems -- 13.1 Introduction -- 13.2 Conformal Wearables for Gait Analysis Quantification and Machine Learning Classification of Hemiplegic Gait -- 13.3 Conformal Wearables for Gait Analysis Quantification and Machine Learning Classification of a Compensatory Hemiplegic Gait Strategy -- 13.4 Conformal Wearables for Quantification of Hemiplegic Reduced Arm Swing During Gait with Machine Learning Classification -- 13.5 Miniaturized Wearables and Wireless Inertial Sensor Systems -- 13.6 Conclusion -- References -- 14 New Developments in Homebound Therapy Enabled Through Wearable and Wireless Systems -- 14.1 Introduction -- 14.2 Contrastive Diagnostics for Distinguishing a Hemiplegic Ankle Pair in Conjunction with Wearable and Wireless Systems with Machine Learning -- 14.3 Patient Specific Response to a Therapy Regimen Through the Application of a Wearable and Wireless System with Machine Learning -- 14.4 Longitudinal Evaluation of the Efficacy of a Therapy Regimen Through the Application of a Wearable and Wireless System with Machine Learning -- 14.5 Observations for Best Practices Regarding Hemiplegic Ankle Rehabilitation -- 14.6 Conclusion -- References -- 15 New Quantifiable Exercise with Wearable and Wireless Systems -- 15.1 Introduction -- 15.2 Conformal Wearables for Enabling Virtual Proprioception for Eccentric Training -- 15.3 Wearable System Applied to Eccentric Strength Training for the Shoulder Press Using Virtual Proprioception -- 15.4 Future Concepts for Augmented Quantified Exercise that Apply Wearable and Wireless Systems -- 15.5 Conclusion. References -- 16 Deep Learning and Spiking Neural Networks for Neuromorphic Applications for Classifying Health Status Using Wearable and Wireless Systems -- 16.1 Introduction -- 16.2 Deep Learning -- 16.3 Neuromorphic Artificial Intelligence -- 16.4 Conclusion -- References -- 17 Future Perspectives for Wearable and Wireless Systems for Healthcare -- 17.1 Introduction -- 17.2 Network Centric Therapy Transition to the Metaverse for Healthcare -- 17.3 Cybersecurity -- 17.4 Blockchain -- 17.5 Smartwatches -- 17.6 Conclusion -- References. |
| Record Nr. | UNINA-9910865264503321 |
LeMoyne Robert
|
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| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Wearable and Wireless Systems for Healthcare I : Gait and Reflex Response Quantification / / by Robert LeMoyne, Timothy Mastroianni
| Wearable and Wireless Systems for Healthcare I : Gait and Reflex Response Quantification / / by Robert LeMoyne, Timothy Mastroianni |
| Autore | LeMoyne Robert |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XIV, 134 p. 34 illus., 24 illus. in color.) |
| Disciplina | 621.382 |
| Collana | Smart Sensors, Measurement and Instrumentation |
| Soggetto topico |
Electrical engineering
Physiotherapy Human physiology Application software Communications Engineering, Networks Human Physiology Information Systems Applications (incl. Internet) |
| ISBN | 981-10-5684-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Wearable and wireless systems for gait analysis and reflex quantification -- Traditional clinical evaluation of gait and reflex response by ordinal scale -- Quantification systems appropriate for a clinical setting -- The rise of inertial measurement units -- Portable wearable and wireless systems for gait and reflex response quantification -- Smartphones and portable media devices as wearable and wireless systems for gait and reflex response quantification -- Bluetooth inertial sensors for gait and reflex response quantification with perspectives regarding Cloud Computing and the Internet of Things -- Quantifying the spatial position representation of gait through sensor fusion -- Role of machine learning for gait and reflex response classification -- Homebound therapy with wearable and wireless systems -- Future perspective of Network Centric Therapy. |
| Record Nr. | UNINA-9910299566303321 |
|
LeMoyne Robert
|
||
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Wearable and Wireless Systems for Healthcare II : Movement Disorder Evaluation and Deep Brain Stimulation Systems / / by Robert LeMoyne, Timothy Mastroianni, Donald Whiting, Nestor Tomycz
| Wearable and Wireless Systems for Healthcare II : Movement Disorder Evaluation and Deep Brain Stimulation Systems / / by Robert LeMoyne, Timothy Mastroianni, Donald Whiting, Nestor Tomycz |
| Autore | LeMoyne Robert |
| Edizione | [2nd ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (204 pages) |
| Disciplina | 621.382 |
| Altri autori (Persone) |
MastroianniTimothy
WhitingDonald TomyczNestor |
| Collana | Smart Sensors, Measurement and Instrumentation |
| Soggetto topico |
Telecommunication
Neurology Human physiology User interfaces (Computer systems) Human-computer interaction Communications Engineering, Networks Human Physiology User Interfaces and Human Computer Interaction |
| ISBN | 981-9746-35-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Wearable and wireless systems for movement disorder evaluation and deep brain stimulation systems -- 2. Movement disorders: Parkinson’s disease and Essential tremor, a general perspective -- 3. Traditional ordinal strategies for establishing the severity and status of movement disorders, such as Parkinson's disease and Essential tremor -- 4. Deep brain stimulation for the treatment of movement disorder regarding Parkinson's disease and Essential tremor with device characterization -- 5. Surgical procedure for deep brain stimulation implantation and operative phase with post-operative risks -- 6. Preliminary wearable and locally wireless systems for quantification of Parkinson's disease and Essential tremor characteristics -- 7. Wearable and wireless systems with Internet connectivity for quantification of Parkinson's disease and Essential tremor characteristics -- 8. Role of machine learning for classification of movement disorderand deep brain stimulation status -- 9. Assessment of machine learning classification strategies for the differentiation of deep brain stimulation ‘On’ and ‘Off’ status for Parkinson’s disease -- 10. New perspectives for Network Centric Therapy for the treatment of Parkinson's disease and Essential tremor -- 11. Advent of Conformal Wearables and Wireless Systems -- 12. Other Notable Innovations for Wearable and Wireless Systems -- 13. Deep Brain Stimulation with Machine Learning Classification Through Conformal Wearables -- 14. Automated Tuning and Optimization of Deep Brain Stimulation -- 15. Other Forms of Neuromodulation -- 16. Future Perspectives. |
| Record Nr. | UNINA-9910882899803321 |
|
LeMoyne Robert
|
||
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Wearable and Wireless Systems for Healthcare II : Movement Disorder Evaluation and Deep Brain Stimulation Systems / / by Robert LeMoyne, Timothy Mastroianni, Donald Whiting, Nestor Tomycz
| Wearable and Wireless Systems for Healthcare II : Movement Disorder Evaluation and Deep Brain Stimulation Systems / / by Robert LeMoyne, Timothy Mastroianni, Donald Whiting, Nestor Tomycz |
| Autore | LeMoyne Robert |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XV, 128 p. 52 illus.) |
| Disciplina | 621.382 |
| Collana | Smart Sensors, Measurement and Instrumentation |
| Soggetto topico |
Electrical engineering
Neurology Human physiology User interfaces (Computer systems) Communications Engineering, Networks Neurology Human Physiology User Interfaces and Human Computer Interaction |
| ISBN | 981-13-5808-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Wearable and wireless systems for movement disorder evaluation and deep brain stimulation systems -- 2. Movement disorders: Parkinson’s disease and Essential tremor, a general perspective -- 3. Traditional ordinal strategies for establishing the severity and status of movement disorders, such as Parkinson's disease and Essential tremor -- 4. Deep brain stimulation for the treatment of movement disorder regarding Parkinson's disease and Essential tremor with device characterization -- 5. Surgical procedure for deep brain stimulation implantation and operative phase with post-operative risks -- 6. Preliminary wearable and locally wireless systems for quantification of Parkinson's disease and Essential tremor characteristics -- 7. Wearable and wireless systems with Internet connectivity for quantification of Parkinson's disease and Essential tremor characteristics -- 8. Role of machine learning for classification of movement disorder and deep brain stimulation status -- 9. Assessment of machine learning classification strategies for the differentiation of deep brain stimulation ‘On’ and ‘Off’ status for Parkinson’s disease -- 10. New perspectives for Network Centric Therapy for the treatment of Parkinson's disease and Essential tremor. |
| Record Nr. | UNINA-9910350276703321 |
|
LeMoyne Robert
|
||
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||