Open Access
An evaluation of the 30-s chair stand test in older adults: frailty detection based on kinematic parameters from a single inertial unit
(BioMed Central, 2013) Millor Muruzábal, Nora; Lecumberri Villamediana, Pablo; Gómez Fernández, Marisol; Martínez Ramírez, Alicia; Izquierdo Redín, Mikel; Matemáticas; Ciencias de la Salud; Matematika; Osasun Zientziak; Gobierno de Navarra / Nafarroako Gobernua
Background: A growing interest in frailty syndrome exists because it is regarded as a major predictor of co-morbidities and mortality in older populations. Nevertheless, frailty assessment has been controversial, particularly when identifying this syndrome in a community setting. Performance tests such as the 30-second chair stand test (30-s CST) are a cornerstone for detecting early declines in functional independence. Additionally, recent advances in body-fixed sensors have enhanced the sensors’ ability to automatically and accurately evaluate kinematic parameters related to a specific movement performance. The purpose of this study is to use this new technology to obtain kinematic parameters that can identify frailty in an aged population through the performance the 30-s CST. Methods: Eighteen adults with a mean age of 54 years, as well as sixteen pre-frail and thirteen frail patients with mean ages of 78 and 85 years, respectively, performed the 30-s CST while threir trunk movements were measured by a sensor-unit at vertebra L3. Sit-stand-sit cycles were determined using both acceleration and orientation information to detect failed attempts. Movement-related phases (i.e. impulse, stand-up, and sit-down) were differentiated based on seat off and seat on events. Finally, the kinematic parameters of the impulse, stand-up and sit-down phases were obtained to identify potential differences across the three frailty groups. Results: For the stand-up and sit-down phases, velocity peaks and “modified impulse” parameters clearly differentiated subjects with different frailty levels (p < 0.001). The trunk orientation range during the impulse phase was also able to classify a subject according to his frail syndrome (p < 0.001). Furthermore, these parameters derived from the inertial units (IUs) are sensitive enough to detect frailty differences not registered by the number of completed cycles which is the standard test outcome. Conclusions: This study shows that IUs can enhance the information gained from tests currently used in clinical practice, such as the 30-s CST. Parameters such as velocity peaks, impulse, and orientation range are able to differentiate between adults and older populations with different frailty levels. This study indicates that early frailty detection could be possible in clinical environments, and the subsequent interventions to correct these disabilities could be prescribed before further degradation occurs.
Open Access
Relevance of sex, age and gait kinematics when predicting fall-risk and mortality in older adults
(Elsevier, 2020) Porta Cuéllar, Sonia; Martínez Ramírez, Alicia; Millor Muruzábal, Nora; Gómez Fernández, Marisol; Izquierdo Redín, Mikel; Ingeniería Eléctrica, Electrónica y de Comunicación; Estadística, Informática y Matemáticas; Ciencias de la Salud; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Estatistika, Informatika eta Matematika; Osasun Zientziak; Gobierno de Navarra / Nafarroako Gobernua, 87/10
Approximately one-third of elderly people fall each year with severe consequences, including death. The aim of this study was to identify the most relevant features to be considered to maximize the accuracy of a logistic regression model designed for prediction of fall/mortality risk among older people. This study included 261 adults, aged over 65 years. Men and women were analyzed separately because sex stratification was revealed as being essential for our purposes of feature ranking and selection. Participants completed a 3-m walk test at their own gait velocity. An inertial sensor attached to their lumbar spine was used to record acceleration data in the three spatial directions. Signal processing techniques allowed the extraction of 21 features representative of gait kinematics, to be used as predictors to train and test the model. Age and gait speed data were also considered as predictors. A set of 23 features was considered. These features demonstrate to be more or less relevant depending on the sex of the cohort under analysis and the classification label (risk of falls and mortality). In each case, the minimum size subset of relevant features is provided to show the maximum accuracy prediction capability. Gait speed has been largely used as the single feature for the prediction fall risk among older adults. Nevertheless, prediction accuracy can be substantially improved, reaching 70% in some cases, if the task of training and testing the model takes into account some other features, namely, sex, age and gait kinematic parameters. Therefore we recommend considering sex, age and step regularity to predict fall-risk.
Open Access
Do frailty and cognitive impairment affect dual-task cost during walking in the oldest old institutionalized patients?
(Springer, 2015-12-14) Lusa Cadore, Eduardo; Casas Herrero, Álvaro; Zambom Ferraresi, Fabrício; Martínez Ramírez, Alicia; Millor Muruzábal, Nora; Gómez Fernández, Marisol; Bays Moneo, Ana Beatriz; Izquierdo Redín, Mikel; Ciencias de la Salud; Osasun Zientziak; Matemáticas; Matematika
Open Access
Valoración de la capacidad funcional en el ámbito domiciliario y en la clínica. Nuevas posibilidades de aplicación de la acelerometría para la valoración de la marcha, equilibrio y potencia muscular en personas mayores
(Gobierno de Navarra, 2008) Izquierdo Redín, Mikel; Martínez Ramírez, Alicia; Larrión, J. L.; Irujo Espinosa, M.; Gómez Fernández, Marisol; Matemáticas; Matematika
Dentro de cualquier población de individuos mayores de 65 años, una proporción sustancial (entre el 6% y el 25%) sufre diferentes síntomas del síndrome de fragilidad. A pesar de la complejidad del termino fragilidad y de las imprecisiones en cuanto a su definición existe un consenso sobre sus síntomas y signos. Las personas que poseen este síndrome presentan pérdidas de fuerza muscular, fatiga, disminución de la actividad física, con un aumento del riesgo de padecer anorexia-pérdida de peso, delirium, hospitalización, declive funcional, deterioro cognitivo, mortalidad, ingreso en residencias, caídas e inestabilidad. Bajo este contexto, surge la necesidad de desarrollar tests que sean capaces de predecir de la forma más precoz posible la fragilidad y la discapacidad. La acelerometría es una herramienta adecuada para la monitorización de movimientos humanos de una forma objetiva y fiable, aplicable en la vida diaria de los sujetos sin implicar grandes costes. Los acelerómetros están siendo utilizados en la monitorización de diferentes movimientos. Se pueden obtener una amplio abanico de medidas como: clasificación de movimientos, valoración del nivel de actividad física, estimación del gasto de energía metabólica, medida del equilibrio, ritmo de marcha y control al levantarse-sentarse. Combinando la acelerometría con giróscopos y magnetómetros se podrá añadir información relacionada con la orientación y los cambios de posición. Esta revisión analiza las herramientas y tecnologías existentes que puedan llegar a detectar de manera precoz posibles signos y síntomas de la fragilidad y permitan a los individuos vivir autónomamente de forma más prolongada y en condiciones de mayor seguridad.
Open Access
Frailty assessment based on trunk kinematic parameters during walking
(BioMed Central, 2015) Martínez Ramírez, Alicia; Martinikorena Aranburu, Ion; Gómez Fernández, Marisol; Lecumberri Villamediana, Pablo; Millor Muruzábal, Nora; Rodríguez Mañas, Leocadio; García García, Francisco José; Izquierdo Redín, Mikel; Matemáticas; Matematika
Background: Physical frailty has become the center of attention of basic, clinical and demographic research due to its incidence level and gravity of adverse outcomes with age. Frailty syndrome is estimated to affect 20 % of the population older than 75 years. Thus, one of the greatest current challenges in this field is to identify parameters that can discriminate between vulnerable and robust subjects. Gait analysis has been widely used to predict frailty. The aim of the present study was to investigate whether a collection of parameters extracted from the trunk acceleration signals could provide additional accurate information about frailty syndrome. Methods: A total of 718 subjects from an elderly population (319 males, 399 females; age: 75.4 ± 6.1 years, mass: 71.8 ± 12.4 kg, height: 158 ± 6 cm) volunteered to participate in this study. The subjects completed a 3-m walk test at their own gait velocity. Kinematic data were acquired from a tri-axial inertial orientation tracker. Findings: The spatio-temporal and frequency parameters measured in this study with an inertial sensor are related to gait disorders and showed significant differences among groups (frail, pre-frail and robust). A selection of those parameters improves frailty classification obtained to gait velocity, compared to classification model based on gait velocity solely. Interpretation: Gait parameters simultaneously used with gait velocity are able to provide useful information for a more accurate frailty classification. Moreover, this technique could improve the early detection of pre-frail status, allowing clinicians to perform measurements outside of a laboratory environment with the potential to prescribe a treatment for reversing their physical decline.