Longitudinal Monitoring of Progressive Supranuclear Palsy using Body-Worn Movement Sensors
© 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society..
BACKGROUND: We have previously shown that wearable technology and machine learning techniques can accurately discriminate between progressive supranuclear palsy (PSP), Parkinson's disease, and healthy controls. To date these techniques have not been applied in longitudinal studies of disease progression in PSP.
OBJECTIVES: We aimed to establish whether data collected by a body-worn inertial measurement unit (IMU) network could predict clinical rating scale scores in PSP and whether it could be used to track disease progression.
METHODS: We studied gait and postural stability in 17 participants with PSP over five visits at 3-month intervals. Participants performed a 2-minute walk and an assessment of postural stability by standing for 30 seconds with their eyes closed, while wearing an array of six IMUs.
RESULTS: Thirty-two gait and posture features were identified, which progressed significantly with time. A simple linear regression model incorporating the three features with the clearest progression pattern was able to detect statistically significant progression 3 months in advance of the clinical scores. A more complex linear regression and a random forest approach did not improve on this.
CONCLUSIONS: The reduced variability of the models, in comparison to clinical rating scales, allows a significant change in disease status from baseline to be observed at an earlier stage. The current study sheds light on the individual features that are important in tracking disease progression. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2022 |
|---|---|
| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:37 |
|---|---|
| Enthalten in: |
Movement disorders : official journal of the Movement Disorder Society - 37(2022), 11 vom: 01. Nov., Seite 2263-2271 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Sotirakis, Charalampos [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Clinical rating scales |
|---|
| Anmerkungen: |
Date Completed 15.11.2022 Date Revised 06.01.2023 published: Print-Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1002/mds.29194 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM34571380X |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM34571380X | ||
| 003 | DE-627 | ||
| 005 | 20231226025711.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2022 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1002/mds.29194 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1152.xml |
| 035 | |a (DE-627)NLM34571380X | ||
| 035 | |a (NLM)36054142 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Sotirakis, Charalampos |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Longitudinal Monitoring of Progressive Supranuclear Palsy using Body-Worn Movement Sensors |
| 264 | 1 | |c 2022 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 15.11.2022 | ||
| 500 | |a Date Revised 06.01.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. | ||
| 520 | |a BACKGROUND: We have previously shown that wearable technology and machine learning techniques can accurately discriminate between progressive supranuclear palsy (PSP), Parkinson's disease, and healthy controls. To date these techniques have not been applied in longitudinal studies of disease progression in PSP | ||
| 520 | |a OBJECTIVES: We aimed to establish whether data collected by a body-worn inertial measurement unit (IMU) network could predict clinical rating scale scores in PSP and whether it could be used to track disease progression | ||
| 520 | |a METHODS: We studied gait and postural stability in 17 participants with PSP over five visits at 3-month intervals. Participants performed a 2-minute walk and an assessment of postural stability by standing for 30 seconds with their eyes closed, while wearing an array of six IMUs | ||
| 520 | |a RESULTS: Thirty-two gait and posture features were identified, which progressed significantly with time. A simple linear regression model incorporating the three features with the clearest progression pattern was able to detect statistically significant progression 3 months in advance of the clinical scores. A more complex linear regression and a random forest approach did not improve on this | ||
| 520 | |a CONCLUSIONS: The reduced variability of the models, in comparison to clinical rating scales, allows a significant change in disease status from baseline to be observed at an earlier stage. The current study sheds light on the individual features that are important in tracking disease progression. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a clinical rating scales | |
| 650 | 4 | |a gait and posture | |
| 650 | 4 | |a inertial measurement units | |
| 650 | 4 | |a kinematic features | |
| 650 | 4 | |a machine learning | |
| 650 | 4 | |a wearable sensors | |
| 700 | 1 | |a Conway, Niall |e verfasserin |4 aut | |
| 700 | 1 | |a Su, Zi |e verfasserin |4 aut | |
| 700 | 1 | |a Villarroel, Mauricio |e verfasserin |4 aut | |
| 700 | 1 | |a Tarassenko, Lionel |e verfasserin |4 aut | |
| 700 | 1 | |a FitzGerald, James J |e verfasserin |4 aut | |
| 700 | 1 | |a Antoniades, Chrystalina A |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Movement disorders : official journal of the Movement Disorder Society |d 1995 |g 37(2022), 11 vom: 01. Nov., Seite 2263-2271 |w (DE-627)NLM012945846 |x 1531-8257 |7 nnns |
| 773 | 1 | 8 | |g volume:37 |g year:2022 |g number:11 |g day:01 |g month:11 |g pages:2263-2271 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1002/mds.29194 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 37 |j 2022 |e 11 |b 01 |c 11 |h 2263-2271 | ||