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Items: 1 to 20 of 61

1.

Indoor Trajectory Reconstruction of Walking, Jogging, and Running Activities Based on a Foot-Mounted Inertial Pedestrian Dead-Reckoning System.

Ceron JD, Martindale CF, López DM, Kluge F, Eskofier BM.

Sensors (Basel). 2020 Jan 24;20(3). pii: E651. doi: 10.3390/s20030651.

2.

A Mobile Solution for Rhythmic Auditory Stimulation Gait Training.

Aholt K, Eskofier BM, Martindale CF, Kuderle A, Gassner H, Gladow T, Rojo J, Villanueva-Mascato S, Klucken J, Arredondo Waldmeyer MT.

Conf Proc IEEE Eng Med Biol Soc. 2019 Jul;2019:309-312. doi: 10.1109/EMBC.2019.8857143.

PMID:
31945903
3.

Estimation of gait kinematics and kinetics from inertial sensor data using optimal control of musculoskeletal models.

Dorschky E, Nitschke M, Seifer AK, van den Bogert AJ, Eskofier BM.

J Biomech. 2019 Oct 11;95:109278. doi: 10.1016/j.jbiomech.2019.07.022. Epub 2019 Aug 1.

PMID:
31472970
4.

Sick Moves! Motion Parameters as Indicators of Simulator Sickness.

Feigl T, Roth D, Gradl S, Wirth M, Latoschik ME, Eskofier BM, Philippsen M, Mutschler C.

IEEE Trans Vis Comput Graph. 2019 Nov;25(11):3146-3157. doi: 10.1109/TVCG.2019.2932224. Epub 2019 Aug 14.

PMID:
31425036
5.

Correction to: Development and clinical validation of inertial sensor-based gait-clustering methods in Parkinson's disease.

Nguyen A, Roth N, Ghassemi NH, Hannink J, Seel T, Klucken J, Gassner H, Eskofier BM.

J Neuroeng Rehabil. 2019 Jul 26;16(1):98. doi: 10.1186/s12984-019-0567-z.

6.

Development and clinical validation of inertial sensor-based gait-clustering methods in Parkinson's disease.

Nguyen A, Roth N, Ghassemi NH, Hannink J, Seel T, Klucken J, Gassner H, Eskofier BM.

J Neuroeng Rehabil. 2019 Jun 26;16(1):77. doi: 10.1186/s12984-019-0548-2. Erratum in: J Neuroeng Rehabil. 2019 Jul 26;16(1):98.

7.

Balance and mobility in geriatric patients : Assessment and treatment of neurological aspects.

Jahn K, Freiberger E, Eskofier BM, Bollheimer C, Klucken J.

Z Gerontol Geriatr. 2019 Jul;52(4):316-323. doi: 10.1007/s00391-019-01561-z. Epub 2019 Jun 3. Review.

PMID:
31161336
8.

Hidden Markov Model-Based Smart Annotation for Benchmark Cyclic Activity Recognition Database Using Wearables.

Martindale CF, Sprager S, Eskofier BM.

Sensors (Basel). 2019 Apr 16;19(8). pii: E1820. doi: 10.3390/s19081820.

9.

Optimal control simulation predicts effects of midsole materials on energy cost of running.

Dorschky E, Krüger D, Kurfess N, Schlarb H, Wartzack S, Eskofier BM, van den Bogert AJ.

Comput Methods Biomech Biomed Engin. 2019 Jun;22(8):869-879. doi: 10.1080/10255842.2019.1601179. Epub 2019 Apr 16.

PMID:
30987457
10.

Perturbation Treadmill Training Improves Clinical Characteristics of Gait and Balance in Parkinson's Disease.

Gaßner H, Steib S, Klamroth S, Pasluosta CF, Adler W, Eskofier BM, Pfeifer K, Winkler J, Klucken J.

J Parkinsons Dis. 2019;9(2):413-426. doi: 10.3233/JPD-181534.

PMID:
30958316
11.

The Diagnostic Scope of Sensor-Based Gait Analysis in Atypical Parkinsonism: Further Observations.

Gaßner H, Raccagni C, Eskofier BM, Klucken J, Wenning GK.

Front Neurol. 2019 Jan 22;10:5. doi: 10.3389/fneur.2019.00005. eCollection 2019.

12.

Treadmill exercise intervention improves gait and postural control in alpha-synuclein mouse models without inducing cerebral autophagy.

Minakaki G, Canneva F, Chevessier F, Bode F, Menges S, Timotius IK, Kalinichenko LS, Meixner H, Müller CP, Eskofier BM, Casadei N, Riess O, Schröder R, Winkler J, Xiang W, von Hörsten S, Klucken J.

Behav Brain Res. 2019 May 2;363:199-215. doi: 10.1016/j.bbr.2018.11.035. Epub 2018 Dec 30.

PMID:
30599154
13.

Comparison of Different Algorithms for Calculating Velocity and Stride Length in Running Using Inertial Measurement Units.

Zrenner M, Gradl S, Jensen U, Ullrich M, Eskofier BM.

Sensors (Basel). 2018 Nov 30;18(12). pii: E4194. doi: 10.3390/s18124194.

14.

Real-time Mental State Recognition using a Wearable EEG.

Richer R, Zhao N, Amores J, Eskofier BM, Paradiso JA.

Conf Proc IEEE Eng Med Biol Soc. 2018 Jul;2018:5495-5498. doi: 10.1109/EMBC.2018.8513653.

PMID:
30441581
15.

Mobile Gait Analysis using Personalised Hidden Markov Models for Hereditary Spastic Paraplegia Patients.

Martindale CF, Roth N, Gasner H, Jensen D, Kohl Z, Eskofier BM.

Conf Proc IEEE Eng Med Biol Soc. 2018 Jul;2018:5430-5433. doi: 10.1109/EMBC.2018.8513508.

PMID:
30441565
16.

Exploring the Feasibility of EMG Based Interaction for Assessing Cognitive Capacity in Virtual Reality.

Wirth M, Grad S, Poimann D, Richer R, Ottmann J, Eskofier BM.

Conf Proc IEEE Eng Med Biol Soc. 2018 Jul;2018:4953-4956. doi: 10.1109/EMBC.2018.8513213.

PMID:
30441454
17.

Movement Speed Estimation Based on Foot Acceleration Patterns.

Grad S, Zrenner M, Schuldhaus D, Wirth M, Cegielny T, Zwick C, Eskofier BM.

Conf Proc IEEE Eng Med Biol Soc. 2018 Jul;2018:3505-3508. doi: 10.1109/EMBC.2018.8513042.

PMID:
30441134
18.

Pre-operative sensor-based gait parameters predict functional outcome after total knee arthroplasty.

Kluge F, Hannink J, Pasluosta C, Klucken J, Gaßner H, Gelse K, Eskofier BM, Krinner S.

Gait Posture. 2018 Oct;66:194-200. doi: 10.1016/j.gaitpost.2018.08.026. Epub 2018 Aug 24.

PMID:
30199778
19.

Sensor-based gait analysis of individualized improvement during apomorphine titration in Parkinson's disease.

Marxreiter F, Gaßner H, Borozdina O, Barth J, Kohl Z, Schlachetzki JCM, Thun-Hohenstein C, Volc D, Eskofier BM, Winkler J, Klucken J.

J Neurol. 2018 Nov;265(11):2656-2665. doi: 10.1007/s00415-018-9012-7. Epub 2018 Sep 8.

PMID:
30196324
20.

Sensor-based gait analysis in atypical parkinsonian disorders.

Raccagni C, Gaßner H, Eschlboeck S, Boesch S, Krismer F, Seppi K, Poewe W, Eskofier BM, Winkler J, Wenning G, Klucken J.

Brain Behav. 2018 Jun;8(6):e00977. doi: 10.1002/brb3.977. Epub 2018 May 7.

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