- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
In: Sensors 17.9 (2017).
- Klassifikation
-
Industrielle und handwerkliche Fertigung
- Schlagwort
-
-
- Ereignis
-
Veröffentlichung
- (wo)
-
Erlangen
- (wer)
-
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
- (wann)
-
2017
- Urheber
- URN
-
urn:nbn:de:bvb:29-opus4-95191
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:45 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Hannink, Julius
- Ollenschläger, Malte
- Kluge, Felix
- Roth, Nils
- Klucken, Jochen
- Eskofier, Bjoern M.
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
Entstanden
- 2017
Ähnliche Objekte (12)
Indoor Trajectory Reconstruction of Walking, Jogging, and Running Activities Based on a Foot-Mounted Inertial Pedestrian Dead-Reckoning System
Data Mining in the U.S. National Toxicology Program (NTP) Database Reveals a Potential Bias Regarding Liver Tumors in Rodents Irrespective of the Test Agent
A Robust Kalman Framework with Resampling and Optimal Smoothing
The Diagnostic Scope of Sensor-Based Gait Analysis in Atypical Parkinsonism: Further Observations
Fall Risk Prediction in Parkinson’s Disease Using Machine Learning and Real-World Inertial Sensor-Based Gait Analysis
Cyclic motion analysis using inertial sensors and machine learning
Hidden Markov Model-Based Smart Annotation for Benchmark Cyclic Activity Recognition Database Using Wearables
Human Activity Recognition Using Binary Sensors, BLE Beacons, an Intelligent Floor and Acceleration Data: A Machine Learning Approach
Hierarchical, Multi-Sensor Based Classification of Daily Life Activities: Comparison with State-of-the-Art Algorithms Using a Benchmark Dataset
Experimental Validation of Real-Time Ski Jumping Tracking System Based on Wearable Sensors
Inertial sensor-based gait parameters reflect patient-reported fatigue in multiple sclerosis
Does the Position of Foot-Mounted IMU Sensors Influence the Accuracy of Spatio-Temporal Parameters in Endurance Running?
Indoor Trajectory Reconstruction of Walking, Jogging, and Running Activities Based on a Foot-Mounted Inertial Pedestrian Dead-Reckoning System
Data Mining in the U.S. National Toxicology Program (NTP) Database Reveals a Potential Bias Regarding Liver Tumors in Rodents Irrespective of the Test Agent
A Robust Kalman Framework with Resampling and Optimal Smoothing
The Diagnostic Scope of Sensor-Based Gait Analysis in Atypical Parkinsonism: Further Observations
Fall Risk Prediction in Parkinson’s Disease Using Machine Learning and Real-World Inertial Sensor-Based Gait Analysis
Cyclic motion analysis using inertial sensors and machine learning
Hidden Markov Model-Based Smart Annotation for Benchmark Cyclic Activity Recognition Database Using Wearables
Human Activity Recognition Using Binary Sensors, BLE Beacons, an Intelligent Floor and Acceleration Data: A Machine Learning Approach
Hierarchical, Multi-Sensor Based Classification of Daily Life Activities: Comparison with State-of-the-Art Algorithms Using a Benchmark Dataset
Experimental Validation of Real-Time Ski Jumping Tracking System Based on Wearable Sensors
Inertial sensor-based gait parameters reflect patient-reported fatigue in multiple sclerosis
Does the Position of Foot-Mounted IMU Sensors Influence the Accuracy of Spatio-Temporal Parameters in Endurance Running?
Indoor Trajectory Reconstruction of Walking, Jogging, and Running Activities Based on a Foot-Mounted Inertial Pedestrian Dead-Reckoning System
Data Mining in the U.S. National Toxicology Program (NTP) Database Reveals a Potential Bias Regarding Liver Tumors in Rodents Irrespective of the Test Agent
A Robust Kalman Framework with Resampling and Optimal Smoothing
The Diagnostic Scope of Sensor-Based Gait Analysis in Atypical Parkinsonism: Further Observations
Fall Risk Prediction in Parkinson’s Disease Using Machine Learning and Real-World Inertial Sensor-Based Gait Analysis
Cyclic motion analysis using inertial sensors and machine learning
Hidden Markov Model-Based Smart Annotation for Benchmark Cyclic Activity Recognition Database Using Wearables
Human Activity Recognition Using Binary Sensors, BLE Beacons, an Intelligent Floor and Acceleration Data: A Machine Learning Approach
Hierarchical, Multi-Sensor Based Classification of Daily Life Activities: Comparison with State-of-the-Art Algorithms Using a Benchmark Dataset
Experimental Validation of Real-Time Ski Jumping Tracking System Based on Wearable Sensors
Inertial sensor-based gait parameters reflect patient-reported fatigue in multiple sclerosis