| Literature DB >> 23039219 |
Agnes Zijlstra1, Martina Mancini, Ulrich Lindemann, Lorenzo Chiari, Wiebren Zijlstra.
Abstract
BACKGROUND: Motion sensors offer the possibility to obtain spatiotemporal measures of mobility-related activities such as sit-stand and stand-sit transitions. However, the application of new sensor-based methods for assessing sit-stand-sit performance requires the detection of crucial events such as seat on/off in the sensor-based data. Therefore, the aim of this study was to evaluate the agreement of detecting sit-stand and stand-sit events based on a novel body-fixed-sensor method with a force-plate based analysis.Entities:
Mesh:
Year: 2012 PMID: 23039219 PMCID: PMC3546014 DOI: 10.1186/1743-0003-9-75
Source DB: PubMed Journal: J Neuroeng Rehabil ISSN: 1743-0003 Impact factor: 4.262
Subject characteristics
| Gender | 6 M, 6 F | 8 M, 2 F |
| Age (years) | 70.3 (59–83) | 70.0 (61–77) |
| Height (cm) | 172.5 (163–187) | 178.2 (159–191) |
| Weight (kg) | 79.8 (62–102) | 85 (67–105) |
Mean, minimum and maximum values are indicated.
Figure 1Event detection in sit-stand-sit transitions. a Trunk angle in the sagittal plane and events T1-T6 for a sit-stand-sit movement performed with arms crossed in front of the trunk by an older subject. b Vertical force signal below feet (black, solid line) and chair (grey, dashed line) and events t1-t6 for the same sit-stand-sit movement. See section ‘data analysis’ for a description of the events.
Figure 2Movement durations estimated from body-fixed-sensor (BFS) data are plotted against those estimated from force-plate data.
Durations and maximum angular velocities in standing-up (SU) and sitting-down (SD)
| | | ||||||
| SU | −0.096 | .925 | |||||
| | | −0.474 | .641 | ||||
| | SD | −0.171 | .866 | ||||
| | | 0.167 | .869 | ||||
| SU | −0.323 | .750 | |||||
| | | −0.397 | .696 | ||||
| | SD | 0.071 | .944 | ||||
| | | 0.143 | .888 | ||||
| | | ||||||
| Flexion | 0.718 | .483 | |||||
| | | −0.428 | .673 | ||||
| | Extension | −0.853 | .404 | ||||
| | | 3.108 | .007* | ||||
| Flexion | −1.603 | .125 | |||||
| | | 3.683 | .001* | ||||
| | Extension | 1.335 | .197 | ||||
| −0.370 | .716 | ||||||
Averaged total durations and corresponding coefficients of variation (CoVs) for the condition with arms crossed in front of the trunk as determined from body-fixed-sensor (BFS) and force-plate data, as well as averaged durations and maximum angular velocities (ωmax) of flexion and extension phases. Mean, standard deviation, minimum and maximum is indicated.
: two-tailed independent samples t-test, * significant difference.
Agreement for body-fixed-sensor and force-plate method in duration estimation of standing-up (SU) and sitting-down (SD)
| | ||||||||
|---|---|---|---|---|---|---|---|---|
| | ||||||||
| SU | 0.417 | 1.725 | .093 | 0.394 | 0.702 | .488 | ||
| | (0.616-0.884) | | | | (0.322-0.797) | | | |
| SD | 0.433 | 4.259 | .000* | 0.346 | 5.467 | .000* | ||
| (0.676-0.904) | (0.528-0.873) | |||||||
Intra-class correlation coefficients (ICCs3,1), corresponding 95% confidence intervals (CIs), limits of agreement (LOAs) and paired samples t-test results for the condition with arms crossed in front of the trunk.
: two-tailed paired samples t-test, * significant difference.
Figure 3Bland-Altman plots showing the differences in movement duration between the body-fixed-sensor (BFS) and force-plate method. a-d A reference line (solid) for the mean of difference between the two methods, lines for plus (upper, dashed) and minus (lower, dashed) 1.96 times the standard deviation of differences, and a linear trend line with the coefficient of determination (R2) are given.
Figure 4Time differences between body-fixed-sensor (T) and force-plate (t) method for detecting sit-stand-sit events (1–6). a-b Older subjects (white boxes), patients with PD (grey boxes). Boxes denote median value, first and third quartile and whiskers denote minimum and maximum value.