Nora Millor

Functional Capacity, Muscle Fat Infiltration, Power Output, and Cognitive Impairment in Institutionalized Frail Oldest Old

This study examined the neuromuscular and functional performance differences between frail oldest old with and without mild cognitive impairment (MCI). In addition, the associations between functional capacities, muscle mass, strength, and power output of the leg muscles were also examined. Forty-three elderly men and women (91.9±4.1 years) were classified into three groups--the frail group, the frail with MCI group (frail+MCI), and the non-frail group. Strength tests were performed for upper and lower limbs. Functional tests included 5-meter habitual gait, timed up-and-go (TUG), dual task performance, balance, and rise from a chair ability. Incidence of falls was assessed using questionnaires. The thigh muscle mass and attenuation were assessed using computed tomography. There were no differences between the frail and frail+MCI groups for all the functional variables analyzed, except in the cognitive score of the TUG with verbal task, which frail showed greater performance than the frail+MCI group. Significant associations were observed between the functional performance, incidence of falls, muscle mass, strength, and power in the frail and frail+MCI groups (r=-0.73 to r=0.83, p<0.01 to p<0.05). These results suggest that the frail oldest old with and without MCI have similar functional and neuromuscular outcomes. Furthermore, the functional outcomes and incidences of falls are associated with muscle mass, strength, and power in the frail elderly population.

Kinematic parameters to evaluate functional performance of sit-to-stand and stand-to-sit transitions using motion sensor devices: a systematic review.

Clinicians commonly use questionnaires and tests based on daily life activities to evaluate physical function. However, the outcomes are usually more qualitative than quantitative and subtle differences are not detectable. In this review, we aim to assess the role of body motion sensors in physical performance evaluation, especially for the sit-to-stand and stand-to-sit transitions. In total, 53 full papers and conference abstracts on related topics were included and 16 different parameters related to transition performance were identified as potentially meaningful to explain certain disabilities and impairments. Transition duration is the most used to evaluate chair-related tests in real clinical settings. High-fall-risk fallers and frail subjects presented longer and more variable transition duration. Other kinematic parameters have also been highlighted in the literature as potential means to detect age-related impairments. In particular, vertical linear velocity and trunk tilt range were able to differentiate between different frailty levels. Frequency domain measures such as spectral edge frequency were also higher for elderly fallers. Lastly, approximate entropy values were larger for subjects with Parkinsons disease and were significantly reduced after treatment. This information could help clinicians in their evaluations as well as in prescribing a physical fitness program to correct a specific deficit.

Automatic Evaluation of the 30-s Chair Stand Test Using Inertial/Magnetic-Based Technology in an Older Prefrail Population

The aim of this study was to evaluate the inertial measures of the 30-s chair stand test using modern body-fixed motion sensors. Polynomial data fitting was used to correct the drift effect in the position estimation. Thereafter, the three most important test cycles phases (“impulse,” “stand up,” and “sit down”) were characterized and automatically analyzed. Automated test control is provided, making it possible for researchers without engineering knowledge to run the test. A collection of meaningful data based on kinematic variables is selected for further research. The proposed methodology for data analysis is a feasible tool for use in clinical settings. This method may not only improve rehabilitation therapies but also identify people at risk for falls more accurately than simply evaluating the number of cycles.

Frailty assessment based on trunk kinematic parameters during walking

BackgroundPhysical 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.MethodsA 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.FindingsThe 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.InterpretationGait 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.

Biomechanical jumping differences among elite female handball players with and without previous anterior cruciate ligament reconstruction: a novel inertial sensor unit study.

Persistent biomechanical and jumping capacity alterations have been observed among female athletes who have sustained anterior cruciate ligament (ACL) injuries. The purpose of this study was to examine if biomechanical jumping differences persist among a cohort of elite female handball players with previous ACL reconstruction several years after return to top-level competition. In order to achieve this goal, a direct mechanics simplified analysis by using a single Inertial Sensor Unit (IU) was used. Twenty-one elite female (6 anterior cruciate ligament reconstructed and 15 uninjured control players) handball players were recruited and evaluated 6.0 ± 3.5 years after surgical anterior cruciate ligament reconstruction. Bilateral and unilateral vertical jumps were performed to evaluate the functional performance and a single inertial sensor unit was employed in order to collect 3D acceleration and 3D orientation data. Previously ACL-reconstructed analysed athletes demonstrated significant (p < 0.05) alterations in relation to the three-dimensional axis (X–Y–Z) supported accelerations and differing jump phase durations, including jumping performance values, in both bilateral and unilateral jumping manoeuvres several years after ACL reconstruction. Identification of the encountered deficits through the use of an IU devise could provide clinicians with a new reliable tool for movement analysis in a clinical setting.

Drift-Free Position Estimation for Periodic Movements Using Inertial Units

Latest advances in microelectromechanical systems have made inertial units (IUs) a powerful tool for human motion analysis. However, difficulties in handling their output signals must be overcome. The purpose of this study was to develop the novel “PB-algorithm” based on polynomial data fitting, splines interpolation, and the wavelet transform, one after the other, to cancel drift disturbances in position estimation for periodic movements. High-accuracy position measurements from an optical system (Vicon Nexus 1.0) were used to validate the proposed method and comparison with another drift-correction algorithm was provided. Results indicate the accuracy with respect to the Vicons reference signal (euclidean error lower than 54.62 × 10 -3 m and correlation coefficient higher than 0.968). A reduction of the root-mean-square error of 68.74% was obtained when the proposed two-step method was compared with a modified-band limited Fourier linear combiner. All methods were applied to data from the 30-s chair stand test, which is one of the most used clinical tests dealing with lower body strength assessment, falls prediction, and gait disorders in older adults. The relevance of this study is that after cancelling drift disturbances, and obtaining an accurate Z-position estimation, it is possible to evaluate the sit-to-stand and stand-to-sit transitions from the whole test.

Gait Velocity and Chair Sit-Stand-Sit Performance Improves Current Frailty-Status Identification

Frailty is characterized by a loss of functionality and is expected to affect 9.9% of people aged 65 and over. Here, current frailty classification is compared with a collection of selected kinematic parameters. A total of 718 elderly subjects (319 males and 399 females; age: 75.4 ± 6.1 years), volunteered to participate in this study and were classified according to Fried’s criteria. Both the 30-s chair stand test (CST) and the 3-m walking test were performed and a set of kinematic parameters were obtained from a single inertial unit. A decision tree analysis was used to: 1) identify the most relevant frailty-related parameters and 2) compare validity of this classification. We found that a selected set of parameters from the 30-s CST (i.e., range of movement, acceleration, and power) were better at identifying frailty status than both the actual outcome of the test (i.e., cycles’ number) and the normally used criteria (i.e., gait speed). For the pre-frail status, AUC improves from 0.531 using the actual test outcome and 0.516 with gait speed to 0.938 with the kinematic parameters criteria. In practice, this could improve the presyndrome identification and perform the appropriate actions to postpone the progression into the frail status.

Dual task gait performance in frail individuals with and without mild cognitive impairment

Background: Several studies have stated that frailty is associated with cognitive impairment. Based on various studies, cognition impairment has been considered as a component of frailty. Other authors have shown that physical frailty is associated with low cognitive performance. Dual task gait tests are used as a strong predictor of falls in either dementia or frailty. Consequently, it is important to investigate dual task walking tests in elderly populations including control robust oldest old, frail oldest old with mild cognitive impairment (MCI) and frail oldest old without MCI. Methods: Dual task walking tests were carried out to examine the association between frailty and cognitive impairment in a population with advanced age. Forty-one elderly men and women participated in this study. The subjects from control, frail with MCI and frail without MCI groups, completed the 5-meter walk test at their own gait velocity. Arithmetic and verbal dual task walking performance was also assessed. Kinematic data were acquired from a unique tri-axial inertial sensor. Results: The spatiotemporal and frequency parameters related to gait disorders did not show any significant differences between frail with and without MCI groups. Conclusions: The evaluation of these parameters extracted from the acceleration signals led us to conclude that these results expand the knowledge regarding the common conditions in frailty and MCI and may highlight the idea that the impairment in walking performance does not depend of frailty and cognitive status.

Frailty Assessment Based on Trunk Accelerometry during Walking

The interest in ageing has been notably increased in the last decade because of the continue increment of life expectancy. Some of its consequences like imparity or frailty have become the center of attention of basic, clinic and poblational investigations due to the incidence level and gravity of the adverse outcomes derived from the age. It is estimated that the frailty syndrome affects to the 20% of the population older than 75 years. It is found that the functional decline derived from this syndrome brings to dependency, institutionalization, hospitalizing and death. Thus, one of the greatest actual challenges in this field is to found parameters that can discriminate between vulnerably and healthy subjects. Frailty causes an accelerated motor impairment. Gait analysis has been widely used to predict frailty. Characteristics like velocity or spatio-temporal parameters obtained with walking force platforms have been significantly considered in the literature. Recently, various studies have revealed that one inertial measurement unit provides relevant information about human movements with a minimum part of the cost and complexity of traditional force platforms. In this way, the aim of the present study is to investigate the applicability of trunk accelerometry for the assessment of spatio-temporal and frequential gait parameters allowing clinicians to perform measurements outside the laboratory environment that could improve the prediction of frailty.

Frailty Detection Using the Instrumented Version of the 30-s Chair Stand Test

Frailty syndrome is regarded as a major predictor of co-morbidities and mortality in older populations. Performance test such as the 30-s chair stand one (30-s CST) are a cornerstone for detecting early decline. However, predictions are normally more qualitative than quantitative. Latest advances in body-fixed sensors lead us to a new dimension of measurements, kinematic parameters that can furnish clinicians by objective information to outperform their diagnostics. In the case of the 30-s CST, it has been demonstrated that an instrumented version of the test is able not only to directly provide the actual outcome, the number of performed cycles, but also other kinematic parameters that can explain the movement performance. This instrumented version involves including an inertial unit which provides acceleration and angular velocity data. However, different steps are necessary to extract meaningful information from those rough data. Here, it is explained the full process to obtain kinematic parameters from the 30-s CST and the ones able to differentiate different frailty levels (i.e. Z-acceleration and Z-velocity peaks and positive and/or negative impulses). The main contribution is that this new quantitative information could be of special help in clinical diagnostics, home care services and/or in a fall risk prevention program.