Marisol Gómez

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.

Frailty assessment based on wavelet analysis during quiet standing balance test

BACKGROUND A standard phenotype of frailty was independently associated with an increased risk of adverse outcomes including comorbidity, disability and with increased risks of subsequent falls and fractures. Postural control deficit measurement during quiet standing has been often used to assess balance and fall risk in elderly frail population. Real time human motion tracking is an accurate, inexpensive and portable system to obtain kinematic and kinetic measurements. The aim of this study was to examine orientation and acceleration signals from a tri-axial inertial magnetic sensor during quiet standing balance tests using the wavelet transform in a frail, a prefail and a healthy population. METHODS Fourteen subjects from a frail population (79±4 years), eighteen subjects from a prefrail population (80±3 years) and twenty four subjects from a healthy population (40±3 years) volunteered to participate in this study. All signals were analyzed using time-frequency information based on wavelet decomposition and principal component analysis. FINDINGS The absolute sum of the coefficients of the wavelet details corresponding to the high frequencies component of orientation and acceleration signals were associated with frail syndrome. INTERPRETATION These parameters could be of great interest in clinical settings and improved rehabilitation therapies and in methods for identifying elderly population with frail syndrome.

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.

Wavelet analysis based on time–frequency information discriminate chronic ankle instability

BACKGROUND Ankle sprains are one of the most common lower extremity injuries. Real time human motion tracking is an accurate, inexpensive and portable system to obtain kinematic and kinetic measurements. The purpose of this study was to discriminate between subjects with chronic ankle instability and subjects with stable ankles through inertial tracking technology and force plates. METHODS Twelve subjects (mean (SD) 23.16 (5.32) years, 174.83 (8.78) cm, 73.58 (17.10) kg) with stable ankles and 13 (mean (SD) 24.69 (5.91) years, 173.31 (9.07) cm, 69.61 (15.32) kg) with chronic ankle instability performed the Star Excursion Balance Test. Time-frequency information based on wavelet decomposition was used for analysing all signals. FINDINGS Dynamic balance impairment associated with chronic ankle instability was observed in the peak amplitude in the wavelet approximation as well as the absolute sum of the coefficients of the wavelet details of the acceleration, orientation and force signals. These results were found despite Star Excursion Balance Test performance during anterior, posteromedial and posterolateral excursions lead to similar specific reach distances in both limbs in either the chronic ankle instability or stable ankle groups. INTERPRETATION These parameters could be of great interest in detecting dynamic balance impairment in individuals at risk of sprains that might otherwise go undetected by only reach distance assessment.

Vertical jumping biomechanical evaluation through the use of an inertial sensor-based technology

ABSTRACT Progress in micro-electromechanical systems has turned inertial sensor units (IUs) into a suitable tool for vertical jumping evaluation. In total, 9 men and 8 women were recruited for this study. Three types of vertical jumping tests were evaluated in order to determine if the data provided by an IU placed at the lumbar spine could reliably assess jumping biomechanics and to examine the validity of the IU compared with force plate platform recordings. Robust correlation levels of the IU-based jumping biomechanical evaluation with respect to the force plate across the entire analysed jumping battery were found. In this sense, significant and extremely large correlations were found when raw data of both IU and force plate-derived normalised force–time curves were compared. Furthermore, significant and mainly moderate correlation levels were also found between both instruments when isolated resultant forces’ peak values of predefined jumping phases of each manoeuvre were analysed. However, Bland and Altman graphical representation demonstrated a systematic error in the distribution of the data points within the mean ±1.96 SD intervals. Using IUs, several biomechanical variables such as the resultant force–time curve patterns of the three different vertical jumps analysed were reliably measured.

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.