Sensor Verification and Analytical Validation of Algorithms to Measure Gait and Balance and Pronation/Supination in Healthy Volunteers
Numerous studies have sought to demonstrate the utility of digital measures of motor function in Parkinson’s disease. Frameworks, such as V3, document digital measure development: technical verification, analytical and clinical validation. We present the results of a study to (1) technically verify accelerometers in an Apple iPhone 8 Plus and ActiGraph GT9X versus an oscillating table and (2) analytically validate software tasks for walking and pronation/supination on the iPhone plus passively detect walking measures with the ActiGraph in healthy volunteers versus human raters. In technical verification, 99.4% of iPhone and 91% of ActiGraph tests show good or excellent agreement versus the oscillating table as the gold standard. For the iPhone software task and algorithms, intraclass correlation coefficients (ICCs) > 0.75 are achieved versus the human raters for measures when walking distance is >10 s and pronation/supination when the arm is rotated more than two times. Passively detected walking start and end time was accurate to approx. 1 s and walking measures were accurate to one unit, e.g., one step. The results suggest that the Apple iPhone and ActiGraph GT9X accelerometers are fit for purpose and that task and passively collected measures are sufficiently analytically valid to assess usability and clinical validity in Parkinson’s patients.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2022 |
|---|---|
| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:22 |
|---|---|
| Enthalten in: |
Sensors (Basel, Switzerland) - 22(2022), 16 vom: 20. Aug. |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Ellis, Robert [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Accelerometer |
|---|
| Anmerkungen: |
Date Completed 29.08.2022 Date Revised 08.03.2023 published: Electronic Citation Status MEDLINE |
|---|
| doi: |
10.3390/s22166275 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM345344308 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM345344308 | ||
| 003 | DE-627 | ||
| 005 | 20231226024844.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2022 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.3390/s22166275 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1151.xml |
| 035 | |a (DE-627)NLM345344308 | ||
| 035 | |a (NLM)36016036 | ||
| 035 | |a (PII)6275 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Ellis, Robert |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Sensor Verification and Analytical Validation of Algorithms to Measure Gait and Balance and Pronation/Supination in Healthy Volunteers |
| 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 29.08.2022 | ||
| 500 | |a Date Revised 08.03.2023 | ||
| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Numerous studies have sought to demonstrate the utility of digital measures of motor function in Parkinson’s disease. Frameworks, such as V3, document digital measure development: technical verification, analytical and clinical validation. We present the results of a study to (1) technically verify accelerometers in an Apple iPhone 8 Plus and ActiGraph GT9X versus an oscillating table and (2) analytically validate software tasks for walking and pronation/supination on the iPhone plus passively detect walking measures with the ActiGraph in healthy volunteers versus human raters. In technical verification, 99.4% of iPhone and 91% of ActiGraph tests show good or excellent agreement versus the oscillating table as the gold standard. For the iPhone software task and algorithms, intraclass correlation coefficients (ICCs) > 0.75 are achieved versus the human raters for measures when walking distance is >10 s and pronation/supination when the arm is rotated more than two times. Passively detected walking start and end time was accurate to approx. 1 s and walking measures were accurate to one unit, e.g., one step. The results suggest that the Apple iPhone and ActiGraph GT9X accelerometers are fit for purpose and that task and passively collected measures are sufficiently analytically valid to assess usability and clinical validity in Parkinson’s patients | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Parkinson’s disease | |
| 650 | 4 | |a accelerometer | |
| 650 | 4 | |a analytical validation | |
| 650 | 4 | |a gait and balance | |
| 650 | 4 | |a pronation | |
| 650 | 4 | |a technical verification | |
| 650 | 4 | |a walking | |
| 700 | 1 | |a Kelly, Peter |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Chengrui |e verfasserin |4 aut | |
| 700 | 1 | |a Pearlmutter, Andrew |e verfasserin |4 aut | |
| 700 | 1 | |a Izmailova, Elena S |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Sensors (Basel, Switzerland) |d 2007 |g 22(2022), 16 vom: 20. Aug. |w (DE-627)NLM187985170 |x 1424-8220 |7 nnns |
| 773 | 1 | 8 | |g volume:22 |g year:2022 |g number:16 |g day:20 |g month:08 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.3390/s22166275 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 22 |j 2022 |e 16 |b 20 |c 08 | ||