Analysis and decomposition of signals obtained by thigh-fixed uni-axial accelerometry during normal walking

Maximal Walking Distance in Persons with a Lower Limb Amputation

The distance one can walk at a time could be considered an important functional outcome in people with a lower limb amputation. In clinical practice, walking distance in daily life is based on self-report (SIGAM mobility grade (Special Interest Group in Amputee Medicine)), which is known to overestimate physical activity. The aim of this study was to assess the number of consecutive steps and walking bouts in persons with a lower limb amputation, using an accelerometer sensor. The number of consecutive steps was related to their SIGAM mobility grade and to the consecutive steps of age-matched controls in daily life. Twenty subjects with a lower limb amputation and ten age-matched controls participated in the experiment for two consecutive days, in their own environment. Maximal number of consecutive steps and walking bouts were obtained by two accelerometers in the left and right trouser pocket, and one accelerometer on the sternum. In addition, the SIGAM mobility grade was determined and the 10 m walking test (10 MWT) was performed. The maximal number of consecutive steps and walking bouts were significantly smaller in persons with a lower limb amputation, compared to the control group (p < 0.001). Only 4 of the 20 persons with a lower limb amputation had a maximal number of consecutive steps in the range of the control group. Although the maximal covered distance was moderately correlated with the SIGAM mobility grade in participants with an amputation (r = 0.61), for 6 of them, the SIGAM mobility grade did not match with the maximal covered distance. The current study indicated that mobility was highly affected in most persons with an amputation and that the SIGAM mobility grade did not reflect what persons with a lower limb amputation actually do in daily life. Therefore, objective assessment of the maximal number of consecutive steps of maximal covered distance is recommended for clinical treatment.

No differences in objective dynamic instability during acceleration of the knee with or without subjective instability post-total knee arthroplasty

INTRODUCTION

Instability after total knee arthroplasty is a critical problem. The purpose of this study was to clarify the stability of implanted knees during walking by comparing differences in dynamic instability during knee acceleration between individuals with or without previously experienced subjective instability, as measured by self-reported questionnaire.

MATERIALS AND METHODS

We examined 92 knees with medial pivot implants. Mean patient age and follow-up duration were 78.4 years and 32.8 months, respectively. An accelerometer was used to investigate the accelerations along three axes; that is, vertical (VT), mediolateral (ML), and anteroposterior (AP) directions in 3-dimensional (3D) space. The analysis in the stance phase and gait cycle was performed by: (1) root mean square (RMS) values of acceleration and (2) frequency domain analysis using fast Fourier transformation (FFT). A self-reported knee instability score was used for the subjective feeling of instability.

RESULTS

A total of 76 knees did not feel unstable (group 0), but 16 knees felt unstable (group 1) in patients during activities of daily living. Regarding the RMS, there were no differences in each direction between the groups. For FFT, the cumulative amplitude in the frequency < 30 Hz also showed no significant differences in all directions between the groups during the stance phase (VT, p = 0.335; ML, p = 0.219; AP, p = 0.523) or gait cycle (VT, p = 0.077; ML, p = 0.082; AP, p = 0.499).

DISCUSSION

Gait analysis based on the acceleration data showed that there were no between-group differences in objective dynamic instability during acceleration of the knee, with or without reports of previously experienced subjective instability, as assessed by the self-reported questionnaire.

Estimating three-dimensional orientation of human body parts by inertial/magnetic sensing

User-worn sensing units composed of inertial and magnetic sensors are becoming increasingly popular in various domains, including biomedical engineering, robotics, virtual reality, where they can also be applied for real-time tracking of the orientation of human body parts in the three-dimensional (3D) space. Although they are a promising choice as wearable sensors under many respects, the inertial and magnetic sensors currently in use offer measuring performance that are critical in order to achieve and maintain accurate 3D-orientation estimates, anytime and anywhere. This paper reviews the main sensor fusion and filtering techniques proposed for accurate inertial/magnetic orientation tracking of human body parts; it also gives useful recipes for their actual implementation.

A symbol-based approach to gait analysis from acceleration signals: identification and detection of gait events and a new measure of gait symmetry

Gait analysis can convey important information about one's physical and cognitive condition. Wearable inertial sensor systems can be used to continuously and unobtrusively assess gait during everyday activities in uncontrolled environments. An important step in the development of such systems is the processing and analysis of the sensor data. This paper presents a symbol-based method used to detect the phases of gait and convey important dynamic information from accelerometer signals. The addition of expert knowledge substitutes the need for supervised learning techniques, rendering the system easy to interpret and easy to improve incrementally. The proposed method is compared to an approach based on peak detection. A new symbol-based symmetry index is created and compared to a traditional temporal symmetry index and a symmetry measure based on cross correlation. The symbol-based symmetry index exemplifies how the proposed method can extract more information from the acceleration signal than previous approaches.

Accelerometry: a technique for quantifying movement patterns during walking

The popularity of using accelerometer-based systems to quantify human movement patterns has increased in recent years for clinicians and researchers alike. The benefits of using accelerometers compared to more traditional gait analysis instruments include low cost; testing is not restricted to a laboratory environment; accelerometers are small, therefore walking is relatively unrestricted; and direct measurement of 3D accelerations eliminate errors associated with differentiating displacement and velocity data. However, accelerometry is not without its disadvantages, an issue which is scarcely reported in gait analysis literature. This paper reviews the use of accelerometer technology to investigate gait-related movement patterns, and addresses issues of acceleration measurement important for experimental design. An overview of accelerometer mechanics is provided before illustrating specific experimental conditions necessary to ensure the accuracy of gait-related acceleration measurement. A literature review is presented on how accelerometry has been used to examine basic temporospatial gait parameters, shock attenuation, and segmental accelerations of the body during walking. The output of accelerometers attached to the upper body has provided useful insights into the motor control of normal walking, age-related differences in dynamic postural control, and gait patterns in people with movement disorders.

Effect of daily physical activity on proximal femur

BACKGROUND

The incidence of osteoporotic fractures is increasing and has become one of the major health problems in developed countries. Physical exercise has been found to be effective in the prevention of osteoporosis. However, the optimal amount of exercise is not known. The aim of this study was to examine the association between the intensity of physical activity and bone mineral density at the proximal femur, using long-term quantification of daily physical activity.

METHODS

The study subjects were 64 women (age 35-40 years), who carried an accelerometer-based body movement recorder for 12 months for individual quantification of their daily physical activity. The average distribution of daily accelerations was defined using 33 acceleration levels.

FINDINGS

A significant relationship between physical activity data and proximal femur bone mineral density was found. Physical activity that induced acceleration levels exceeding 3.6g correlated positively with the bone mineral density change at the proximal femur, the association being strongest at the femoral neck at 5.7 g (r = 0.416, P = 0.001).

INTERPRETATION

The association between physical activity and changes in proximal femur bone mineral density was dependent on the acceleration level of exercise. The quantity and quality of exercise can be monitored with the accelerometer-based physical activity monitor, and the method might be used for optimizing exercise for prevention of osteoporosis.

Intensity of exercise is associated with bone density change in premenopausal women

INTRODUCTION

High-impact exercise is known to be beneficial for bones. However, the optimal amount of exercise is not known. The aim of the present study was to evaluate the association between the intensity of exercise and bone mineral density (BMD).

METHODS

We performed a 12-month population-based trial with 120 women (aged 35-40 years) randomly assigned to an exercise group or to a control group. The intensity of the physical activity of 64 women was assessed with an accelerometer-based body movement monitor. The daily activity was analyzed at five acceleration levels (0.3-1.0 g, 1.1-2.4 g, 2.5-3.8 g, 3.9-5.3 g, and 5.4-9.2 g). BMD was measured at the hip, spine (L1-L4), and radius by dual-energy x-ray absorptiometry. The calcaneus was measured using quantitative ultrasound.

RESULTS

Physical activity that induced acceleration levels exceeding 3.9 g correlated positively with the BMD change in the hip area (p<0.05-0.001). L1 BMD change correlated positively with activity exceeding 5.4 g (p<0.05) and calcaneal speed of sound with the level of 1.1-2.4 g (p< 0.05). Baseline BMD was negatively associated with the BMD change at the hip.

CONCLUSION

The intensity of exercise, measured as the acceleration level of physical activity, was significantly correlated with BMD changes. Bone stimulation is reached during normal physical exercise in healthy premenopausal women. In the hip area, the threshold level for improving BMD is less than 100 accelerations per day at levels exceeding 3.9 g.

Ambulatory motor assessment in Parkinson's disease

We developed an algorithm that distinguishes between on and off states in patients with Parkinson's disease during daily life activities. Twenty-three patients were monitored continuously in a home-like situation for approximately 3 hours while they carried out normal daily-life activities. Behavior and comments of patients during the experiment were used to determine the on and off periods by a trained observer. Behavior of the patients was measured using triaxial accelerometers, which were placed at six different positions on the body. Parameters related to hypokinesia (percentage movement), bradykinesia (mean velocity), and tremor (percentage peak frequencies above 4 Hz) were used to distinguish between on and off states. The on-off detection was evaluated using sensitivity and specificity. The performance for each patient was defined as the average of the sensitivity and specificity. The best performance to classify on and off states was obtained by analysis of movements in the frequency domain with a sensitivity of 0.97 and a specificity of 0.97. We conclude that our algorithm can distinguish between on and off states with a sensitivity and specificity near 0.97. This method, together with our previously published method to detect levodopa-induced dyskinesia, can automatically assess the motor state of Parkinson's disease patients and can operate successfully in unsupervised ambulatory conditions.

Automated estimation of initial and terminal contact timing using accelerometers; development and validation in transtibial amputees and controls

The aim of this study was to develop and validate an automated accelerometry-based system for estimating initial contact (IC) and terminal contact (TC) timing information from walking patterns of healthy control subjects and transtibial amputees that can be used in daily life with minimal interference of researchers. Subjects were instrumented with two uniaxial accelerometers just below the knee while synchronized ground reaction force (GRF) recordings were used as reference measurements. An automated multiphase algorithm was developed to estimate the time of IC and TC in the acceleration signals of five healthy subjects and two transtibial amputees walking at different walking speeds. The accuracy of the detection algorithm in ten control subjects and eight transtibial amputees indicated mean errors ranging between 0.013 and 0.034 s for the TC and IC timing, with 95 % confidence interval of the individual step errors ranging between -0.062 and 0.115 s. Correlation coefficients between the estimated stance phase duration and GRF data were 0.98 and 0.97 for controls and amputees, respectively. We concluded that IC and TC can be accurately and easily measured using this system in both healthy subjects and transtibial amputees walking at different walking speeds. The system can be used in clinical situations or gait labs as well as during daily life.

Analysis and decomposition of accelerometric signals of trunk and thigh obtained during the sit-to-stand movement

Piezoresistive accelerometer signals are frequently used in movement analysis. However, their use and interpretation are complicated by the fact that the signal is composed of different acceleration components. The aim of the study was to obtain insight into the components of accelerometer signals from the trunk and thigh segments during four different sit-to-stand (STS) movements (self-selected, slow, fast and fullflexion). Nine subjects performed at least six trials of each type of STS movement. Accelerometer signals from the trunk and thigh in the sagittal direction were decomposed using kinematic data obtained from an opto-electronic device. Each acceleration signal was decomposed into gravitational and inertial components, and the inertial component of the trunk was subsequently decomposed into rotational and translational components. The accelerometer signals could be reliably reconstructed: mean normalised root mean square (RMS) trunk: 6.5% (range 3-12%), mean RMS thigh: 3% (range 2-5%). The accelerometric signals were highly characteristic and repeatable. The influence of the inertial component was significant, especially on the timing of the specific event of maximum trunk flexion in the accelerometer signal. The effect of inertia was larger in the trunk signal than in the thigh signal and increased with higher speeds. The study provides insight into the acceleration signal, its components and the influence of the type of STS movement and supports its use in STS movement analysis.

The accuracy of measuring the kinematics of rising from a chair with accelerometers and gyroscopes

The purpose of this study was to assess the accuracy of measuring angle and angular velocity of the upper body and upper leg during rising from a chair with accelerometers, using low-pass filtering of the accelerometer signal. Also, the improvement in accuracy of the measurement with additional use of high-pass filtered gyroscopes was assessed. Two uni-axial accelerometers and one gyroscope (DynaPort) per segment were used to measure angles and angular velocities of upper body and upper leg. Calculated angles and angular velocities were compared to a high-quality optical motion analysis system (Optotrak), using root mean squared error (RMS) and correlation coefficient (r) as parameters. The results for the sensors showed that two uni-axial accelerometers give a reasonable accurate measurement of the kinematics of rising from a chair (RMS = 2.9, 3.5, and 2.6 degrees for angle and RMS = 9.4, 18.4, and 11.5 degrees /s for angular velocity for thorax, pelvis, and upper leg, respectively). Additional use of gyroscopes improved the accuracy significantly (RMS = 0.8, 1.1, and 1.7 degrees for angle and RMS = 2.6, 4.0 and 4.9 degrees /s for angular velocity for thorax, pelvis and upper leg, respectively). The low-pass Butterworth filter had optimal cut-off frequencies of 1.05, 1.3, and 1.05 for thorax, pelvis, and upper leg, respectively. For the combined signal, the optimal cut-off frequencies were 0.18, 0.2, and 0,38 for thorax, pelvis and upper leg, respectively. The filters showed no subject specificity. This study provides an accurate, inexpensive and simple method to measure the kinematics of movements similar to rising from a chair.

Motion artefact reduction of the photoplethysmographic signal in pulse transit time measurement

Motion artefact is a common occurrence that contaminates photoplethysmographic (PPG) measurements. To extract timing information from signals during artefact is challenging. PPG signal is very sensitive to artefacts and can be used in applications like, pulse transit time (PTT) as part of the polysomnographic studies. A correlation cancellation or signal processing approach is implemented with the adaptive cancelling filter concept and a triaxial accelerometry. PPG signals obtained from a Masimo (Reference) pulse oximeter is used as reference to compare with the reconstructed PPG signals. Different hands are used for each PPG source, one stationary while the other involves typical movements during sleep. A second Masimo pulse oximeter is used to register intensity of timing errors on commercial PPG signals. 108 PTT measurements are recorded in three different movements with PTT estimates from unprocessed PPG signals showing 35.51+/-27.42%, Masimo 50.02+/-29.40% and reconstructed 4.32+/-3.59% difference against those from the Reference PPG. The triaxial accelerometry can be used to detect the presence of artefact on PPG signals. This is useful in PTT measurements when signal contaminated with artefacts are required for further analysis, especially after and during arousals in sleep. The suggested filtering model can then reconstruct these corrupted PPG signals.

Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement

Accelerometry offers a practical and low cost method of objectively monitoring human movements, and has particular applicability to the monitoring of free-living subjects. Accelerometers have been used to monitor a range of different movements, including gait, sit-to-stand transfers, postural sway and falls. They have also been used to measure physical activity levels and to identify and classify movements performed by subjects. This paper reviews the use of accelerometer-based systems in each of these areas. The scope and applicability of such systems in unsupervised monitoring of human movement are considered. The different systems and monitoring techniques can be integrated to provide a more comprehensive system that is suitable for measuring a range of different parameters in an unsupervised monitoring context with free-living subjects. An integrated approach is described in which a single, waist-mounted accelerometry system is used to monitor a range of different parameters of human movement in an unsupervised setting.

Measuring daily behavior using ambulatory accelerometry: the Activity Monitor

Advanced ambulatory systems that measure aspects of overt human behavior during normal daily life have become feasible, owing to developments in data recording and sensor technology. One such instrument is the Activity Monitor (AM). This paper provides a technical description of the AM and information about its validity and current applications. The AM is based on ambulatory accelerometry, the aim of which is to assess postures and motions for long-term (> 24-h) measurement periods during normal daily life. Accelerometers are attached to the thighs, trunk, and lower arms, and signals are continuously stored in a digital portable recorder. In the postmeasurement analysis, postures and motions are detected by means of custom-made software programs. Validity studies performed on different populations showed high agreement scores between the computerized and automatic AM output and the visually analyzed video recordings. The AM has so far been applied in rehabilitation, psychophysiology, and cardiology but has many possibilities in behavioral research.