S138 Abstracts / Gait & Posture 39S (2014) S1–S141

Fig. 2. BTS Smart movement imaging using the Davis modified model.

The kinematic parameters were registered with BTS Smartmovement analysis system (Fig. 2). The registration of five mus-cle groups electrical activity in left and right lower limb (m.vastusmedialis oblique, m.rectus femoris, plantar flexor group, ham-strings, lateral dorsal flexor group) was carried out with telemetricEMG measurement system NORAXON TeleMyo 2400 G2.

Results: 180 movement cycles were registered for each trainingdevice.

Discussion and conclusions: The measurements results sug-gest there is a statistically significant difference between muscleactivation (EMG), range of motion and joint angles in the movementcycles performed on two tested training devices. The registeredmuscle activation patterns give the opportunity to be comparedwith muscle activation patterns in the same muscle groups duringskiing reported in literature [2].

Reference

[1] Bober T, Rutkowska-Kucharska A, Pietraszewski B. Cwiczenia plyometryczne– charakterystyka biomechaniczna, wskazniki zastosowania. Sport wyczynowy2007;7–9:511–3.

[2] Panizzolo FA, et al. Comparative analysis of muscle activation patterns betweenskiing on slopes and on training devices. Proc Eng 2010;2:2537–42.

http://dx.doi.org/10.1016/j.gaitpost.2014.04.197

P82

A longitudinal study of gait function in peoplewith Alzheimer disease

Ylva Cedervall 1,∗, Kjartan Halvorsen 2, AnnaCristina Åberg 1

1 Department of Public Health and CaringSciences/Geriatrics, Uppsala University, Sweden2 Department of Information Technology, UppsalaUniversity, Sweden

Introduction and aim: Executive and attention dysfunctionshave been suggested to be the main cause of early gait impairmentsand falls in people with Alzheimer’s disease (AD). Walking in dailylife, places high demands on the interplay between cognitive andmotor functions. A well-functioning ability to dual-tasking is thusessential for walking safely. Identifying changes in gait functionduring dual-tasking may guide the design of interventions aimedat fall prevention, and contribute to maintaining physical functionand among people with AD. The aims were, to study longitudinalchanges in gait parameters during single- and dual-task conditionsover a period of two years among people with initially mild AD.

Patients/materials and methods: Twenty-one individuals withmild AD (Mini Mental State Examination: 21–30), 10 male/11female: 55–78 years, were included. The data collection was con-

Fig. 1. The cross-sectional differences between gait speed at single – task namesand dual-task animals.

Fig. 2. The dual task cost percent for naming animals. The horizontal line indicatesa reference value (9%) for healthy older adults.

ducted on three occasions, 12 months apart. A Qualisys® motioncapture system, a three-dimensional optical gait analysis system,was used. Reflecting markers were applied on anatomical land-marks according to a standardized procedure. The participantwalked barefoot a distance of 7 m. A six camera Pro Reflex® sys-tem recorded the position of the markers at a sampling frequencyof 240 Hz. At each gait occasion, the following gait parameters werecomputed: gait speed, step width, -length, -height, and doublesupport time. All gait parameters were examined at the partici-pant’s comfortable gait speed during three different conditions; fivesingle-task trials, three dual-task trials naming names, and threedual-task trials naming animals. The mean values of 3–4 steps inthe middle part of each trial were analysed.

Results: There was a significant decline in gait speed and steplength during single- and dual-tasking. In contrast, no significantlongitudinal change could be found in dual-task cost (single-taskvalue–dual-task value). However, the cross-sectional differencesbetween single- and dual-tasks gait parameters were significantfor 9/10 comparisons at baseline, 8/10 at the one-year follow-up,and 9/10 at the two-year follow-up. The significant differencesfor all gait parameters were observed between the one- and thetwo-year follow-ups. Systematic visual examination of the motioncapture files revealed that the gait speed slowing in dual-taskingincluded, e.g. general hesitating, intermittent stops in single- anddouble stance (Figs. 1 and 2).

Discussion and conclusions: Gait function was found to bemarkedly affected in early years of AD. In addition to a slowedgait speed, an evident impact of dual-tasking was shown. How-ever, the dual-task cost appeared to remain stable over time. Thiswas unexpected and could be hypothesized to reflect a diminish-ing ability to adjust walking to declining cognitive function. Variousgait pattern disturbances were observed during dual-tasking andcontributed to the slowed gait speed, and may also increase fall risk.Future research may be focused on identification of people at riskof AD by the use of dual-task methods, and on dual-task walkingperformances to identify fall risk in AD.

http://dx.doi.org/10.1016/j.gaitpost.2014.04.198