Automatic real-time monitoring and assessment of tremor parameters in the upper limb from orientation data
Upper limb tremor is the most prevalent movement disorder and, unfortunately, it is not effectively managed in a large proportion of the patients. Neuroprostheses that stimulate the sensorimotor pathways are one of the most promising alternatives although they are still under development. To enrich...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2014-07-01
|
| Series: | Frontiers in Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00221/full |
| _version_ | 1811201356455739392 |
|---|---|
| author | Stefan eLambrecht Juan Álvaro eGallego Eduardo eRocon Jose L. Pons |
| author_facet | Stefan eLambrecht Juan Álvaro eGallego Eduardo eRocon Jose L. Pons |
| author_sort | Stefan eLambrecht |
| collection | DOAJ |
| description | Upper limb tremor is the most prevalent movement disorder and, unfortunately, it is not effectively managed in a large proportion of the patients. Neuroprostheses that stimulate the sensorimotor pathways are one of the most promising alternatives although they are still under development. To enrich the interpretation of data recorded during long-term tremor monitoring and to increase the intelligence of tremor suppression neuroprostheses we need to be aware of the context. Context awareness is a major challenge for neuroprostheses and would allow these devices to react more quickly and appropriately to the changing demands of the user and/or task. Traditionally kinematic features are used to extract context information, with most recently the use of joint angles as highly potential features. In this paper we present two algorithms that enable the robust extraction of joint angle and related features to enable long-term continuous monitoring of tremor with context awareness. First, we describe a novel relative sensor placement identification technique based on orientation data. We focus on relative rather than absolute sensor location, because in many medical applications magnetic and inertial measurement units (MIMU) are used in a chain stretching over adjacent segments, or are always placed on a fixed set of locations. Subsequently we demonstrate how tremor parameters can be extracted from orientation data using an adaptive estimation algorithm. Relative sensor location was detected with an accuracy of 94.12% for the 4 MIMU configuration, and 100% for the 3 MIMU configurations. Kinematic tracking error values with an average deviation of 8% demonstrate our ability to estimate tremor from orientation data. The methods presented in this study constitute an important step towards more user-friendly and context-aware neuroprostheses for tremor suppression and monitoring. |
| first_indexed | 2024-04-12T02:20:30Z |
| format | Article |
| id | doaj.art-d58a70afe79040b884da06b2628ba9e5 |
| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-04-12T02:20:30Z |
| publishDate | 2014-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj.art-d58a70afe79040b884da06b2628ba9e52022-12-22T03:52:09ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2014-07-01810.3389/fnins.2014.0022191078Automatic real-time monitoring and assessment of tremor parameters in the upper limb from orientation dataStefan eLambrecht0Juan Álvaro eGallego1Eduardo eRocon2Jose L. Pons3Spanish National Research Council CSICSpanish National Research Council CSICSpanish National Research Council CSICSpanish National Research Council CSICUpper limb tremor is the most prevalent movement disorder and, unfortunately, it is not effectively managed in a large proportion of the patients. Neuroprostheses that stimulate the sensorimotor pathways are one of the most promising alternatives although they are still under development. To enrich the interpretation of data recorded during long-term tremor monitoring and to increase the intelligence of tremor suppression neuroprostheses we need to be aware of the context. Context awareness is a major challenge for neuroprostheses and would allow these devices to react more quickly and appropriately to the changing demands of the user and/or task. Traditionally kinematic features are used to extract context information, with most recently the use of joint angles as highly potential features. In this paper we present two algorithms that enable the robust extraction of joint angle and related features to enable long-term continuous monitoring of tremor with context awareness. First, we describe a novel relative sensor placement identification technique based on orientation data. We focus on relative rather than absolute sensor location, because in many medical applications magnetic and inertial measurement units (MIMU) are used in a chain stretching over adjacent segments, or are always placed on a fixed set of locations. Subsequently we demonstrate how tremor parameters can be extracted from orientation data using an adaptive estimation algorithm. Relative sensor location was detected with an accuracy of 94.12% for the 4 MIMU configuration, and 100% for the 3 MIMU configurations. Kinematic tracking error values with an average deviation of 8% demonstrate our ability to estimate tremor from orientation data. The methods presented in this study constitute an important step towards more user-friendly and context-aware neuroprostheses for tremor suppression and monitoring.http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00221/fullTremorMEMSsensor locationcontext awarenessreal-time estimation |
| spellingShingle | Stefan eLambrecht Juan Álvaro eGallego Eduardo eRocon Jose L. Pons Automatic real-time monitoring and assessment of tremor parameters in the upper limb from orientation data Frontiers in Neuroscience Tremor MEMS sensor location context awareness real-time estimation |
| title | Automatic real-time monitoring and assessment of tremor parameters in the upper limb from orientation data |
| title_full | Automatic real-time monitoring and assessment of tremor parameters in the upper limb from orientation data |
| title_fullStr | Automatic real-time monitoring and assessment of tremor parameters in the upper limb from orientation data |
| title_full_unstemmed | Automatic real-time monitoring and assessment of tremor parameters in the upper limb from orientation data |
| title_short | Automatic real-time monitoring and assessment of tremor parameters in the upper limb from orientation data |
| title_sort | automatic real time monitoring and assessment of tremor parameters in the upper limb from orientation data |
| topic | Tremor MEMS sensor location context awareness real-time estimation |
| url | http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00221/full |
| work_keys_str_mv | AT stefanelambrecht automaticrealtimemonitoringandassessmentoftremorparametersintheupperlimbfromorientationdata AT juanalvaroegallego automaticrealtimemonitoringandassessmentoftremorparametersintheupperlimbfromorientationdata AT eduardoerocon automaticrealtimemonitoringandassessmentoftremorparametersintheupperlimbfromorientationdata AT joselpons automaticrealtimemonitoringandassessmentoftremorparametersintheupperlimbfromorientationdata |