Movement Intensity in the Minutes Before a Fall: A Lag-Controlled, Activity-Matched Time-Stratified Case-Crossover Analysis of Home Monitoring in Multiple Sclerosis

Background: Fall-risk research in multiple sclerosis usually asks who falls and does not address what changes in the minutes before a fall. Methods: We analyzed continuous home inertial monitoring of 26 people with multiple sclerosis using a time-stratified case-crossover design. Each fall was compared with referent windows from the same participant on other days at the same clock time. Results: After one participant whose accelerometer was not on a 1 g scale was excluded, 48 falls and 285 referents remained in 12 informative strata. Per standard deviation, gravity-removed dynamic acceleration had an odds ratio of 3.05 (95% CI 1.66–5.63). The estimate persisted when the window ended 10, 30, or 60 s before the annotated fall, although these designs overlap the primary one and are not independent tests. Referents from pre-fall days only gave 3.46 (1.67–7.16). When activity was held comparable, the estimate fell to 2.11 (1.17–3.79) within ambulatory windows and to 1.38 (0.86–2.22, p = 0.183) against referents from walking periods. Conclusions: These results suggest that much of the association reflects the fact that people fall while they are moving. No released fall lies in unrecorded time, which indicates that the public dataset retains sensor-captured falls.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Medicine
Published
2026-10-26
DOI
https://doi.org/10.3390/jcm15218323
Primary Topic
Balance, Gait, and Falls Prevention
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Movement Intensity in the Minutes Before a Fall: A Lag-Controlled, Activity-Matched Time-Stratified Case-Crossover Analysis of Home Monitoring in Multiple Sclerosis

Irina Naskinova, Mikhail Kolev, Meglena D. Lazarova, Hristo Kalinov et al.
Journal of Clinical Medicine
Balance, Gait, and Falls Prevention
article

Movement Intensity in the Minutes Before a Fall: A Lag-Controlled, Activity-Matched Time-Stratified Case-Crossover Analysis of Home Monitoring in Multiple Sclerosis

Irina Naskinova, Mikhail Kolev, Meglena D. Lazarova, Hristo Kalinov, Velin Klisurov
article en

Abstract

Background: Fall-risk research in multiple sclerosis usually asks who falls and does not address what changes in the minutes before a fall. Methods: We analyzed continuous home inertial monitoring of 26 people with multiple sclerosis using a time-stratified case-crossover design. Each fall was compared with referent windows from the same participant on other days at the same clock time. Results: After one participant whose accelerometer was not on a 1 g scale was excluded, 48 falls and 285 referents remained in 12 informative strata. Per standard deviation, gravity-removed dynamic acceleration had an odds ratio of 3.05 (95% CI 1.66–5.63). The estimate persisted when the window ended 10, 30, or 60 s before the annotated fall, although these designs overlap the primary one and are not independent tests. Referents from pre-fall days only gave 3.46 (1.67–7.16). When activity was held comparable, the estimate fell to 2.11 (1.17–3.79) within ambulatory windows and to 1.38 (0.86–2.22, p = 0.183) against referents from walking periods. Conclusions: These results suggest that much of the association reflects the fact that people fall while they are moving. No released fall lies in unrecorded time, which indicates that the public dataset retains sensor-captured falls.

Journal of Clinical MedicineVol. 15(21)
University of Architecture, Civil Engineering and Geodesy (BG), Technical University of Sofia (BG), University of Warmia and Mazury in Olsztyn (PL), Sofia University "St. Kliment Ohridski" (BG)
Openalex Percentile: Top 5%
Balance, Gait, and Falls Prevention
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon