Gait dynamics to optimize fall risk assessment in geriatric patients admitted to an outpatient diagnostic clinic

Kikkert, Lisette H J; Groot, Maartje H. de; Campen, Jos P. C. M. van; Beijnen, Jos H.; Hortobágyi, Tibor; Vuillerme, Nicolas; Lamoth, Claudine J. C.

doi:10.1371/journal.pone.0178615

Cited by 42 publications

(38 citation statements)

References 46 publications

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“…In the present study, we use the term ‘gait dynamics’, and refer to outcomes that are indicative of the dynamic nature of the gait pattern and reflect overall gait coordination, adaptability, and the ability to accurately respond to perturbations. Gait dynamics can discriminate young and old adults [ 9 ], individuals with and without a clinical condition [ 10 ], fallers and non-fallers [ 8 , 11 – 14 ], and older adults with and without cognitive disorders [ 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment

Kikkert

Vuillerme

Campen

et al. 2017

J NeuroEngineering Rehabil

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Background: A detailed gait analysis (e.g., measures related to speed, self-affinity, stability, and variability) can help to unravel the underlying causes of gait dysfunction, and identify cognitive impairment. However, because geriatric patients present with multiple conditions that also affect gait, results from healthy old adults cannot easily be extrapolated to geriatric patients. Hence, we (1) quantified gait outcomes based on dynamical systems theory, and (2) determined their discriminative power in three groups: healthy old adults, geriatric patients with-and geriatric patients without cognitive impairment. Methods: For the present cross-sectional study, 25 healthy old adults recruited from community (65 ± 5.5 years), and 70 geriatric patients with (n = 39) and without (n = 31) cognitive impairment from the geriatric dayclinic of the MC Slotervaart hospital in Amsterdam (80 ± 6.6 years) were included. Participants walked for 3 min during singleand dual-tasking at self-selected speed while 3D trunk accelerations were registered with an IPod touch G4. We quantified 23 gait outcomes that reflect multiple gait aspects. A multivariate model was built using Partial Least Square-Discriminant Analysis (PLS-DA) that best modelled participant group from gait outcomes. Results: For single-task walking, the PLS-DA model consisted of 4 Latent Variables that explained 63 and 41% of the variance in gait outcomes and group, respectively. Outcomes related to speed, regularity, predictability, and stability of trunk accelerations revealed with the highest discriminative power (VIP > 1). A high proportion of healthy old adults (96 and 93% for single-and dual-task, respectively) was correctly classified based on the gait outcomes. The discrimination of geriatric patients with and without cognitive impairment was poor, with 57% (single-task) and 64% (dual-task) of the patients misclassified. Conclusions: While geriatric patients vs. healthy old adults walked slower, and less regular, predictable, and stable, we found no differences in gait between geriatric patients with and without cognitive impairment. The effects of multiple comorbidities on geriatric patients' gait possibly causes a 'floor-effect', with no room for further deterioration when patients develop cognitive impairment. An accurate identification of cognitive status thus necessitates a multifactorial approach.

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Section: Introductionmentioning

confidence: 99%

Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment

Kikkert

Vuillerme

Campen

et al. 2017

J NeuroEngineering Rehabil

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“…According current literature data, low bone mineral density [13,26,27] and increased risk of fall [28,29] are connected with impaired physical performance and both of them increase the risk of future VF. In addition, it was demonstrated early, that, regular exercises are effective non-pharmacological measures in prevention of bone loss and osteoporotic fractures [29][30][31].…”

Section: Resultsmentioning

confidence: 99%

“…In addition, it was demonstrated early, that, regular exercises are effective non-pharmacological measures in prevention of bone loss and osteoporotic fractures [29][30][31]. Nowadays, the different tests of physical performance are use for assessment of balancing, coordination, muscle strength and risk of fall in patients with osteoporosis and its complications [14,16,26,28]. Thus, the literature data show that vertebral pain syndrome and associated restriction of physical activity in patients with osteoporosis and its complication (VF) adversely affects the disease progression and life expectancy, as immobilization or low level of physical activity are independent factors of the risk of accelerated bone loss, falls and fractures.…”

Section: Resultsmentioning

confidence: 99%

Vertebral pain syndrome and physical performance assessing in older women with vertebral fractures

Nataliia¹

2017

J Sports Med Ther

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The purpose of this study was to assess the peculiarities of vertebral pain syndrome, parameters of physical performance and quality of life indices in women of older age depending on the presence of vertebral fractures (VF). This study was performed with participation of 215 women aged 50-89 years old which were divided into two groups: fi rst one-women without any previous osteoporotic fractures (n=143), second group -patients with VF in thoracic and/or lumbar spine (n=72).The presence and intensity of pain in the thoracic and lumbar spine were evaluated using the 11-component visual analog scale (VAS), physical performance-with following functional tests: 3-, 4-and 15-meter tests (gait speed), static balance (a side-by-side position, a semi-tandem position and a full-tandem position), 8-feet test and «fi ve timed chair stands» (coordination and strength), hand grip strength (by dynamometer), measurement of arterial pressure (systolic and diastolic), heart and respiratory rates, breath holding, chest excursion (mean and on the inhalation and the exhalation), lateral trunk lean, Schober and Thomayer tests.It was demonstrated that the intensity of vertebral pain (pain at the time of investigation, the most common level of pain, pain in the best periods of the disease) and some physical performance tests (lateral trunk lean and chest excursion (mean index, during the inhalation and exhalation), hand grip strength, 15-meter gait speed test and fi ve-repetition sit-to-stand test) are signifi cantly worse in women with VF than corresponding parameters in persons without fractures. It should be taken into account during the assessment of physical performance and development of rehabilitation programs for older age women with vertebral fractures.

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“…Future studies should focus on applying pattern recognition methods to identify gait abnormalities in different patient populations based on broader types of parameters reflecting the different domains of the ICF e.g. the Fall Efficacy Scale (FES_I), the Charlson Comorbidity index and further cognition tests 5,40 .…”

Section: Discussionmentioning

confidence: 99%

The detection of age groups by dynamic gait outcomes using machine learning approaches

Zhou

Romijnders

Hansen

et al. 2020

Sci Rep

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prevalence of gait impairments increases with age and is associated with mobility decline, fall risk and loss of independence. for geriatric patients, the risk of having gait disorders is even higher. consequently, gait assessment in the clinics has become increasingly important. the purpose of the present study was to classify healthy young-middle aged, older adults and geriatric patients based on dynamic gait outcomes. Classification performance of three supervised machine learning methods was compared. From trunk 3D-accelerations of 239 subjects obtained during walking, 23 dynamic gait outcomes were calculated. Kernel principal component Analysis (KpcA) was applied for dimensionality reduction of the data for Support Vector Machine (SVM) classification. Random Forest (RF) and Artificial Neural Network (ANN) were applied to the 23 gait outcomes without prior data reduction. Classification accuracy of SVM was 89%, RF accuracy was 73%, and ANN accuracy was 90%. Gait outcomes that significantly contributed to classification included: Root Mean Square (Anterior-Posterior, Vertical), cross entropy (Medio-Lateral, Vertical), Lyapunov exponent (Vertical), step regularity (Vertical) and gait speed. ANN is preferable due to the automated data reduction and significant gait outcome identification. For clinicians, these gait outcomes could be used for diagnosing subjects with mobility disabilities, fall risk and to monitor interventions. Over the last decades, medical and technical developments have extended human lifespan. However, with the increasing number of adults in society, there is a parallel increase in the number of people with serious impairments of mobility, gait, and postural control 1. Natural aging comes hand in hand with mobility decline and impairments in gait and postural control. When the level of decline in physical and cognitive functions exceeds the degree of decline expected due to the natural aging process, we speak of a geriatric condition. Typical geriatric patients are characterized by co-morbidities such as sarcopenia, cognitive impairment, osteoporosis, weight loss, and frailty 2,3. Gait disorders are common in older adults; prevalence increases with age and is associated with increased fall risk, mobility decline, and loss of independence 4. For geriatric patients, the risk of having gait disorders with an increased fall incidence is even higher 5. Consequently, objective gait assessment in the clinics has become increasingly important for the diagnosis of motor impairments and the assessment of mobility decline and fall risk 6 , as well as for the monitoring of the efficacy of interventions designed to improve mobility 7. The most often used gait parameter for disability is gait speed. After age 60, gait speed slows by 16% per decade 8. In geriatric patients, a gait speed below 1.0 m/s signifies an additional clinical or sub-clinical impairment, such as mobility decline, frailty, recurrent falling, loss of independence and institutionalization 9. Complementary to gait speed, aging impacts th...

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Gait dynamics to optimize fall risk assessment in geriatric patients admitted to an outpatient diagnostic clinic

Cited by 42 publications

References 46 publications

Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment

Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment

Vertebral pain syndrome and physical performance assessing in older women with vertebral fractures

The detection of age groups by dynamic gait outcomes using machine learning approaches

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