Quantitative Assessment of Head Tremor in Patients with Essential Tremor and Cervical Dystonia by Using Inertial Sensors
Tremor is most common among the movement disabilities that affect older people, having a prevalence rate of 4.6% in the population older than 65 years. Despite this, distinguishing different types of tremors is clinically challenging, often leading to misdiagnosis. However, due to advances in microe...
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MDPI AG
2019-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/19/4246 |
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| author | Lazar Berbakov Čarna Jovanović Marina Svetel Jelena Vasiljević Goran Dimić Nenad Radulović |
| author_facet | Lazar Berbakov Čarna Jovanović Marina Svetel Jelena Vasiljević Goran Dimić Nenad Radulović |
| author_sort | Lazar Berbakov |
| collection | DOAJ |
| description | Tremor is most common among the movement disabilities that affect older people, having a prevalence rate of 4.6% in the population older than 65 years. Despite this, distinguishing different types of tremors is clinically challenging, often leading to misdiagnosis. However, due to advances in microelectronics and wireless communication, it is now possible to easily monitor tremor in hospitals and even in home environments. In this paper, we propose an architecture of a system for remote health-care and one possible implementation of such system focused on head tremor monitoring. In particular, the aim of the study presented here was to test new tools for differentiating essential tremor from dystonic tremor. To that aim, we propose a number of temporal and spectral features that are calculated from measured gyroscope signals, and identify those that provide optimal differentiation between two groups. The mean signal amplitude feature results in sensitivity = 0.8537 and specificity = 0.8039 in distinguishing patients having cervical dystonia with or without tremor. In addition, mean signal amplitude was shown to be significantly higher in patients with essential tremor than in patients with cervical dystonia, whereas the mean peak frequency is not different between two groups. |
| first_indexed | 2024-04-13T06:19:02Z |
| format | Article |
| id | doaj.art-68448b790785402191c753596152dcc9 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T06:19:02Z |
| publishDate | 2019-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-68448b790785402191c753596152dcc92022-12-22T02:58:42ZengMDPI AGSensors1424-82202019-09-011919424610.3390/s19194246s19194246Quantitative Assessment of Head Tremor in Patients with Essential Tremor and Cervical Dystonia by Using Inertial SensorsLazar Berbakov0Čarna Jovanović1Marina Svetel2Jelena Vasiljević3Goran Dimić4Nenad Radulović5Institute Mihailo Pupin, University of Belgrade, Volgina 15, 11050 Belgrade, SerbiaClinic of Neurology, School of Medicine, University of Belgrade, 11000 Belgrade, SerbiaClinic of Neurology, School of Medicine, University of Belgrade, 11000 Belgrade, SerbiaInstitute Mihailo Pupin, University of Belgrade, Volgina 15, 11050 Belgrade, SerbiaInstitute Mihailo Pupin, University of Belgrade, Volgina 15, 11050 Belgrade, SerbiaMath Modeling, 11000 Belgrade, SerbiaTremor is most common among the movement disabilities that affect older people, having a prevalence rate of 4.6% in the population older than 65 years. Despite this, distinguishing different types of tremors is clinically challenging, often leading to misdiagnosis. However, due to advances in microelectronics and wireless communication, it is now possible to easily monitor tremor in hospitals and even in home environments. In this paper, we propose an architecture of a system for remote health-care and one possible implementation of such system focused on head tremor monitoring. In particular, the aim of the study presented here was to test new tools for differentiating essential tremor from dystonic tremor. To that aim, we propose a number of temporal and spectral features that are calculated from measured gyroscope signals, and identify those that provide optimal differentiation between two groups. The mean signal amplitude feature results in sensitivity = 0.8537 and specificity = 0.8039 in distinguishing patients having cervical dystonia with or without tremor. In addition, mean signal amplitude was shown to be significantly higher in patients with essential tremor than in patients with cervical dystonia, whereas the mean peak frequency is not different between two groups.https://www.mdpi.com/1424-8220/19/19/4246neurological tremorambient assisted livingremote healthcareessential tremorcervical dystonia |
| spellingShingle | Lazar Berbakov Čarna Jovanović Marina Svetel Jelena Vasiljević Goran Dimić Nenad Radulović Quantitative Assessment of Head Tremor in Patients with Essential Tremor and Cervical Dystonia by Using Inertial Sensors Sensors neurological tremor ambient assisted living remote healthcare essential tremor cervical dystonia |
| title | Quantitative Assessment of Head Tremor in Patients with Essential Tremor and Cervical Dystonia by Using Inertial Sensors |
| title_full | Quantitative Assessment of Head Tremor in Patients with Essential Tremor and Cervical Dystonia by Using Inertial Sensors |
| title_fullStr | Quantitative Assessment of Head Tremor in Patients with Essential Tremor and Cervical Dystonia by Using Inertial Sensors |
| title_full_unstemmed | Quantitative Assessment of Head Tremor in Patients with Essential Tremor and Cervical Dystonia by Using Inertial Sensors |
| title_short | Quantitative Assessment of Head Tremor in Patients with Essential Tremor and Cervical Dystonia by Using Inertial Sensors |
| title_sort | quantitative assessment of head tremor in patients with essential tremor and cervical dystonia by using inertial sensors |
| topic | neurological tremor ambient assisted living remote healthcare essential tremor cervical dystonia |
| url | https://www.mdpi.com/1424-8220/19/19/4246 |
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