Fear of Falling among Community-dwelling Sedentary and Active Older People

Araya, Alejandra; Iriarte, Evelyn

doi:10.17533/udea.iee.v39n1e13

Cited by 8 publications

(5 citation statements)

References 24 publications

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“…All EPs were functionally independent. A total of 46 participants presented mild KOA (low FOF (13), moderate FOF ( 16), and high FOF (17), and 23 moderate KOA participants (low FOF (4), moderate FOF (6), and high FOF (13). All participants showed homogeneous characteristics in their variables that represent them.…”

Section: Resultsmentioning

confidence: 99%

“…The scores that characterize the different levels of FOF observed in Table 2 show low FOF levels in 17 participants (KOA mild (13) and KOA moderate (4)), a moderate level of FOF ( 22) (KOA mild (16) and KOA moderate ( 6)), and a high level of FOF ( 30) participants (KOA mild (17) and KOA moderate (3)).…”

Section: Resultsmentioning

confidence: 99%

“…In this research paper, we will refer in general terms to FOF [10][11][12]. It can be defined as a cognitive-perceptual state in which there is the idea of a risk of falling (when standing up or walking), generating avoidance behaviors to move, and thus limiting interaction with the environment, restricting movement precisely to avoid falling [13][14][15][16][17]. Although the preoccupation related to the fall is usually something that can actually occur in specific situations (such as unstable surfaces, degree of movement difficulty, and use of cognitive resources, among others), certain conditions have been studied that can exacerbate this condition, such as status cognitive, history of falls, mood, physical performance, and comorbidities [18,19].…”

Section: Introductionmentioning

confidence: 99%

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Classification of Center of Mass Acceleration Patterns in Older People with Knee Osteoarthritis and Fear of Falling

González-Olguín

Rodríguez

Córdoba³

et al. 2022

IJERPH

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(1) Background: The preoccupation related to the fall, also called fear of falling (FOF) by some authors is of interest in the fields of geriatrics and gerontology because it is related to the risk of falling and subsequent morbidity of falling. This study seeks to classify the acceleration patterns of the center of mass during walking in subjects with mild and moderate knee osteoarthritis (KOA) for three levels of FOF (mild, moderate, and high). (2) Method: Center-of-mass acceleration patterns were recorded in all three planes of motion for a 30-meter walk test. A convolutional neural network (CNN) was implemented for the classification of acceleration signals based on the different levels of FOF (mild, moderate, and high) for two KOA conditions (mild and moderate). (3) Results: For the three levels of FOF to fall and regardless of the degree of KOA, a precision of 0.71 was obtained. For the classification considering the three levels of FOF and only for the mild KOA condition, a precision of 0.72 was obtained. For the classification considering the three levels of FOF and only the moderate KOA condition, a precision of 0.81 was obtained, the same as in the previous case, and finally for the classification for two levels of FOF, a high vs. moderate precision of 0.78 was obtained. For high vs. low, a precision of 0.77 was obtained, and for the moderate vs. low, a precision of 0.8 was obtained. Finally, when considering both KOA conditions, a 0.74 rating was obtained. (4) Conclusions: The classification model based on deep learning (CNN) allows for the adequate discrimination of the acceleration patterns of the moderate class above the low or high FOF.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Classification of Center of Mass Acceleration Patterns in Older People with Knee Osteoarthritis and Fear of Falling

González-Olguín

Rodríguez

Córdoba³

et al. 2022

IJERPH

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“…It can change one's perspective on their surroundings and may also be another reason for falls to occur again. [27] This is due to the trauma that can affect their mental health. Falls can happen anywhere.…”

Section: A Fall Riskmentioning

confidence: 99%

Automatic Fall Risk Detection Based on Imbalanced Data

Liu¹,

Hung

Iqbal

et al. 2021

IEEE Access

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In recent years, the declining birthrate and aging population have gradually brought countries into an ageing society. Regarding accidents that occur amongst the elderly, falls are an essential problem that quickly causes indirect physical loss. In this paper, we propose a pose estimation-based fall detection algorithm to detect fall risks. We use body ratio, acceleration and deflection as key features instead of using the body keypoints coordinates. Since fall data is rare in real-world situations, we train and evaluate our approach in a highly imbalanced data setting. We assess not only different imbalanced data handling methods but also different machine learning algorithms. After oversampling on our training data, the K-Nearest Neighbors (KNN) algorithm achieves the best performance. The F1 scores for three different classes, Normal, Fall, and Lying, are 1.00, 0.85 and 0.96, which is comparable to previous research. The experiment shows that our approach is more interpretable with the key feature from skeleton information. Moreover, it can apply in multi-people scenarios and has robustness on medium occlusion.

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“…Mesmo diante dos malefícios da inatividade física, uma grande parcela da população apresenta o comportamento sedentário, tendo dificuldade de adesão a prática regular de atividade física, minimizando a qualidade de vida e, tendo como resultado, a maior probabilidade de doenças de caráter biopsicossocial (Araya et al, 2021). A inatividade física, atualmente, mostra-se como um dos principais responsáveis por Educación Física y Ciencia, julio-septiembre 2022, vol.…”

Section: Introductionunclassified

Efeito da corrida de rua na qualidade de vida: um estudo descritivo e exploratório

Santos

Araújo²,

Santos³

et al. 2022

Educ. fís. cienc.

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Objetivo: verificar a influência da corrida de rua na qualidade de vida. Métodos: trata-se de um estudo transversal, descritivo, com delineamento exploratório, do tipo survey, que observou 118 praticantes de corrida de rua, selecionados de forma não-probabilística e por conveniência. Onde foi aplicado um questionário sociodemográfico, semiestruturado, para a descrição dos participantes, e para verificar a qualidade de vida, foi aplicado o questionário SF-36. A normalidade dos dados foi verificada aplicando o texto Shapiro Wilk, homogeneidade pelo teste de Levene’s (distribuição normal). Os valores foram apresentados em média e desvio padrão para caracterização da amostra geral e por gênero. Todos os testes foram realizados a partir do SPSS Versão 20.0. Resultados: Não foram observadas diferenças significativas da qualidade de vida entre os gêneros. O tempo de prática apresentou correlação significante com a capacidade funcional (p=0,001) e a redução da limitação dos aspectos físicos (p=0,005). Conclusão: A corrida de rua apresenta um importante impacto na qualidade de vida dos praticantes, quando realizada de modo regular. Os benefícios extrapolam o âmbito biodinâmico, gerando benefícios em variáveis psicossociais.

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Fear of Falling among Community-dwelling Sedentary and Active Older People

Cited by 8 publications

References 24 publications

Classification of Center of Mass Acceleration Patterns in Older People with Knee Osteoarthritis and Fear of Falling

Classification of Center of Mass Acceleration Patterns in Older People with Knee Osteoarthritis and Fear of Falling

Automatic Fall Risk Detection Based on Imbalanced Data

Efeito da corrida de rua na qualidade de vida: um estudo descritivo e exploratório

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