Accelerometry-based gait analysis predicts falls among patients with a recent fracture who are ambulatory

Matsumoto, Hiromi; Makabe, Tomoyuki; Morita, Tetsuji; Ikuhara, Kanae; Kajigase, Akira; Okamoto, Yoshihiro; Ashikawa, Eiichi; Kobayashi, Eri; Hagino, Hiroshi

doi:10.1097/mrr.0000000000000099

Cited by 17 publications

(9 citation statements)

References 33 publications

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“…However, this occurs to maintain stability despite aging-associated alterations in the neuromotor, muscular and proprioceptive functions [28]. However, if the recorded acceleration does not increase, the sequencing of the gait has not been altered [26,31]. This instrument allows us to identify early changes in spatiotemporal gait parameters.…”

Section: Discussionmentioning

confidence: 99%

Identification of Body Balance Deterioration of Gait in Women Using Accelerometers

et al. 2020

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This study presents a simple methodology for the evaluation of gait with accelerometers, for rapid and simple application, in which we employ current balance tests in clinical practice (Timed Up and Go, Chair Stand Test and Six-Minute Walk Test). The aim was to determine whether the accelerometric valuation of gait can detect alterations in balance. The sample of this cross-sectional research, made during the months of May and June 2018, was composed of 145 healthy adult women (x = 63.8 ± 8.41 years), from the city of Ourense (Spain). They walked with a triaxial accelerometer at the fourth lumbar vertebra for a distance of 20 m. The test was repeated three times, and the mean of the three measurements was used in the analysis. There was a reduction in the values of acceleration recorded along all three of the axes and in the root mean square as the age increased. This reduction was very significant for the minimum values registered along the vertical and transverse axes, and for the maximum values along the mediolateral axis. Only the maximum values of the vector module demonstrated significant differences among the three age groups. A regression model allowed us to identify the values that give more information on the Timed Up and Go Test, namely: the maximum values of the root mean square and the mediolateral axis. An exhaustive analysis of the vertical and mediolateral axes and the vector module allows for the detection of early alterations in the automatic gait pattern.

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Section: Discussionmentioning

confidence: 99%

Identification of Body Balance Deterioration of Gait in Women Using Accelerometers

et al. 2020

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“…Previous studies had used trunk acceleration data with AC method [33] in patients with transfemoral amputation [36], stroke [37], foot wear prescription [13], and total hip replacement [38]. The AC coefficient of trunk acceleration in the VT axis was found to be a fall predictor in patients with a vertebral or hip fracture [39]. However, few studies concerning trunk movement symmetry and regularity in ankle fracture patients had been found in the current literature.…”

Section: Discussionmentioning

confidence: 99%

“…In the present study, between-steps trunk movement symmetry in VT direction was significantly lower in patients with ankle fracture. Reduced plantar flexor moment at the injured ankle joint could interfere with heel contact [1]; weakness of lower trunk muscles such as iliopsoas and gluteal muscles could lead to poor control of vertical acceleration of the centre of gravity during the loading and mid-stance phases of the gait cycle [39]. Decreased range of motion, reduced peak muscle torque, and muscle atrophy of the ankle following immobilization after ankle fracture might be related to displacement of centre of gravity in the sagittal plane, consequently interfering with between-steps trunk movement symmetry in VT axis [40–42].…”

Section: Discussionmentioning

confidence: 99%

Differences in gait and trunk movement between patients after ankle fracture and healthy subjects

et al. 2019

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Background: Studies have shown that gait asymmetry and activity limitation can persist several months or years after ankle fracture. However, evidence of gait and trunk movement patterns following ankle fracture during the early rehabilitation period is scarce. Thus, we compared gait patterns and trunk movement during the early phase of rehabilitation between patients with ankle fracture and matched controls. Methods: Ten patients with ankle fractures, and ten age-and sex-matched healthy controls were prospectively enrolled. An automated infrared-assisted, trunk accelerometer-based gait analysis system was used to measure walking speed, step length, and cadence. The median time of the evaluation following ankle fracture was 4.0 months. Trunk movement intensity was evaluated as acceleration root mean square. Trunk movement symmetry and regularity were analysed using the autocorrelation method. Differences in gait characteristics between the patient and control groups were analysed using the Mann-Whitney U test. Follow-up assessment of falls was performed 24 months after the fracture. The correlations between Lower Extremity Functional Scale (LEFS) scores/falls and gait parameters were evaluated using Spearman's rank correlation coefficient. Results: Walking speed (p = 0.019), step length (p = 0.023), cadence (p = 0.003), and trunk movement intensity in anterior-posterior and vertical axis (p = 0.001, p = 0.003, respectively) were all significantly lower in the ankle fracture group than in the control group. Trunk movement symmetry in vertical direction (p = 0.019) decreased significantly in patients with ankle fractures, whereas between-strides regularity did not differ between groups. LEFS scores were moderately correlated with walking speed (r = 0.60, p = 0.044) and step length (r = 0.68, p = 0.021). During the 24 months after the fracture, 3 falls were reported by 3 patients. Trunk acceleration root mean square ratio in mediolateral axis (r = 0.72, p = 0.018) was highly correlated with future falls. Conclusion: During early rehabilitation, patients with ankle fracture may develop trunk movement asymmetry in the vertical direction accompanied with slower walking speed and cadence, and smaller step lengths, which can contribute to muscular imbalances and potential injury. Thus, proper rehabilitation strategies should be employed for these patients.

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“…One hypothesis is that balance dysfunction and poor postural control account for inconsistent stepping patterns and therefore drive a greater gait variability [ 29 , 30 ]. As a consequence the stride-to-stride variability of gait parameters have also been found to be useful [ 31 ], despite differing measures of standard deviation [ 32 ] or coefficient of variation being used to examine fall related gait behaviour [ 33 , 34 ].…”

Section: Introductionmentioning

confidence: 99%

Walking orientation randomness metric (WORM) score: pilot study of a novel gait parameter to assess walking stability and discriminate fallers from non-fallers using wearable sensors

Mobbs

Natarajan

Fonseka

et al. 2022

BMC Musculoskelet Disord

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Background Musculoskeletal disorders can contribute to injurious falls and incur significant societal and healthcare burdens. Identification of fallers from non-fallers through wearable-based gait analysis can facilitate timely intervention to assist mobility and prevent falls whilst improving care and attention for high fall-risk patients. In this study, we use wearable sensor-based gait analysis to introduce a novel variable to assess walking stability in fallers and non-fallers – the Walking Orientation Randomness Metric. The WORM score quantifies the stability, or ‘figure-of-eight’ motion of a subject’s trunk during walking as an indicator of a falls-predictive (pathological) gait. Methods WORM is calculated as the ‘figure-of-eight’ oscillation mapped out in the transverse-plane by the upper body’s centre-point during a walking bout. A sample of patients presenting to the Prince of Wales Hospital (Sydney, Australia) with a primary diagnosis of “falls for investigation” and age-matched healthy controls (non-fallers) from the community were recruited. Participants were fitted at the sternal angle with the wearable accelerometer, MetaMotionC (Mbientlab Inc., USA) and walked unobserved (at self-selected pace) for 5-50 m along an obstacle-free, carpeted hospital corridor. Results Participants comprised of 16 fallers (mean age: 70 + 17) and 16 non-fallers (mean age: 70 + 9) based on a recent fall(s) history. The (median) WORM score was 17-fold higher (p < 0.001) in fallers (3.64 cm) compared to non-fallers (0.21 cm). ROC curve analyses demonstrate WORM can discriminate fallers from non-fallers (AUC = 0.97). Diagnostic analyses (cut-off > 0.51 cm) show high sensitivity (88%) and specificity (94%). Conclusion In this pilot study we have introduced the WORM score, demonstrating its discriminative performance in a preliminary sample size of 16 fallers. WORM is a novel gait metric assessing walking stability as measured by truncal way during ambulation and shows promise for objective and clinical evaluation of fallers.

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Accelerometry-based gait analysis predicts falls among patients with a recent fracture who are ambulatory

Cited by 17 publications

References 33 publications

Identification of Body Balance Deterioration of Gait in Women Using Accelerometers

Identification of Body Balance Deterioration of Gait in Women Using Accelerometers

Differences in gait and trunk movement between patients after ankle fracture and healthy subjects

Walking orientation randomness metric (WORM) score: pilot study of a novel gait parameter to assess walking stability and discriminate fallers from non-fallers using wearable sensors

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