Does Accelerometry at the Centre of Mass Accurately Predict the Gait Energy Expenditure in Patients with Hemiparesis?

BACKGROUND: The aim of this study was to compare energy expenditure (EE) predicted by accelerometery (EEAcc) with indirect calorimetry (EEMETA) in individuals with hemiparesis. METHODS: Twenty-four participants (12 with stroke and 12 healthy controls) performed a six-minute walk test (6MWT) during which EEMETA was measured using a portable indirect calorimetry system and EEACC was calculated using Bouten's equation (1993) with data from a three-axis accelerometer positioned between L3 and L4. RESULTS: The median EEMETA was 9.85 [8.18;11.89] W·kg-1 in the stroke group and 5.0 [4.56;5.46] W·kg-1 in the control group. The median EEACC was 8.57 [7.86;11.24] W·kg-1 in the control group and 8.2 [7.05;9.56] W·kg-1 in the stroke group. The EEACC and EEMETA were not significantly correlated in either the control (p = 0.8) or the stroke groups (p = 0.06). The Bland-Altman method showed a mean difference of 1.77 ± 3.65 W·kg-1 between the EEACC and EEMETA in the stroke group and -2.08 ± 1.59 W·kg-1 in the controls. CONCLUSIONS: The accuracy of the predicted EE, based on the accelerometer and the equations proposed by Bouten et al., was low in individuals with hemiparesis and impaired gait. This combination (sensor and Bouten's equation) is not yet suitable for use as a stand-alone measure in clinical practice for the evaluation of hemiparetic patients.

Energy cost of obstacle crossing in stroke patients.

OBJECTIVE: The purpose of this study was to analyze the effects of clearing and skirting obstacles during the gait on the energetic cost of walking (ECW) of patients with chronic hemiplegia. The hypothesis was that hemiplegia would have a greatest increase in the ECW than in the healthy group. DESIGN: Fifteen healthy subjects and 17 patients with chronic hemiplegia completed two 6-min walking sessions: one with obstacles and the other without obstacles. During both sessions, the patients were equipped with a portable gas analyzer to measure oxygen uptake (V˙o2). Gait velocity and ECW were calculated. RESULTS: In both groups, gait velocity was lower in the with-obstacles condition and the ECW was significantly higher. V˙o2 was greater in the with-obstacles condition for the healthy group, whereas it remained unchanged for the group with hemiplegia. CONCLUSIONS: Results demonstrated that the addition of obstacles during gait increased the ECW and decreased mean walking speed in both the healthy subjects and the patients with hemiplegia. More interestingly, the authors found differences in adaptation strategies between the healthy subjects and the patients with hemiplegia. During the with-obstacles condition, the oxygen uptakes of the healthy subjects increased and mean walking speed decreased, whereas, in the subjects with hemiplegia, only mean walking speed decreased.