Highlights ► We examined the validity of the Microsoft Kinect for assessing postural control. ► Data were collected during functional reach and standing balance tasks. ► Results from the Microsoft Kinect and a 3D motion analysis system were compared. ► Comparable inter-trial reliability and excellent concurrent validity were observed.
Highlights • We tested the accuracy of Kinect to measure motion in Parkinson's disease. • The Kinect accurately measured the timing and range of large movements. • The Kinect did not measure smaller movements as accurately. • The Kinect has potential to be a low-cost, home-based sensor to measure movement.
Abstract Impaired standing balance has a detrimental effect on a person's functional ability and increases their risk of falling. There is currently no validated system which can precisely quantify center of pressure (COP), an important component of standing balance, while being inexpensive, portable and widely available. The Wii Balance Board (WBB) fits these criteria, and we examined its validity in comparison with the ‘gold standard’—a laboratory-grade force platform (FP). Thirty subjects without lower limb pathology performed a combination of single and double leg standing balance tests with eyes open or closed on two separate occasions. Data from the WBB were acquired using a laptop computer. The test–retest reliability for COP path length for each of the testing devices, including a comparison of the WBB and FP data, was examined using intraclass correlation coefficients (ICC), Bland–Altman plots (BAP) and minimum detectable change (MDC). Both devices exhibited good to excellent COP path length test–retest reliability within-device (ICC = 0.66–0.94) and between-device (ICC = 0.77–0.89) on all testing protocols. Examination of the BAP revealed no relationship between the difference and the mean in any test, however the MDC values for the WBB did exceed those of the FP in three of the four tests. These findings suggest that the WBB is a valid tool for assessing standing balance. Given that the WBB is portable, widely available and a fraction of the cost of a FP, it could provide the average clinician with a standing balance assessment tool suitable for the clinical setting.
Highlights • We surveyed the literature for clinical applications of wearable systems. • Wearable sensing can identify movement disorders and assess surgical outcomes. • Wearable feedback can improve walking stability and reduce joint loading. • Future work should implement in natural environments such as home or work.
Highlights • Kinect sensor was used as a markerless motion capture system (MLS). • Results were compared with marker based system (MBS). • Four kind of motions were performed. • Measured range of motion was found statistically different between systems. • MLS reproducibility was found to be statistically similar to MBS.
Abstract Summary of background data The analysis of centre of pressure (COP) excursions is used as an index of postural stability in standing. Conflicting data have been reported over the past 20 years regarding the reliability of COP measures and no standard procedure for COP measure use in study design has been established. Search methods Six online databases (January 1980 to February 2009) were systematically searched followed by a manual search of retrieved papers. Results Thirty-two papers met the inclusion criteria. The majority of the papers (26/32, 81.3%) demonstrated acceptable reliability. While COP mean velocity (mVel) demonstrated variable but generally good reliability throughout the different studies ( r = 0.32–0.94), no single measurement of COP appeared significantly more reliable than the others. Regarding data acquisition duration, a minimum of 90 s is required to reach acceptable reliability for most COP parameters. This review further suggests that while eyes closed readings may show slightly higher reliability coefficients, both eyes open and closed setups allow acceptable readings under the described conditions ( r ≥ 0.75). Also averaging the results of three to five repetitions on firm surface is necessary to obtain acceptable reliability. A sampling frequency of 100 Hz with a cut-off frequency of 10 Hz is also recommended. No final conclusion regarding the feet position could be reached. Conclusions The studies reviewed show that bipedal static COP measures may be used as a reliable tool for investigating general postural stability and balance performance under specific conditions. Recommendations for maximizing the reliability of COP data are provided.
Abstract Background/Aim Three-dimensional kinematic measures of gait are routinely used in clinical gait analysis and provide a key outcome measure for gait research and clinical practice. This systematic review identifies and evaluates current evidence for the inter-session and inter-assessor reliability of three-dimensional kinematic gait analysis (3DGA) data. Method A targeted search strategy identified reports that fulfilled the search criteria. The quality of full-text reports were tabulated and evaluated for quality using a customised critical appraisal tool. Results Fifteen full manuscripts and eight abstracts were included. Studies addressed both within-assessor and between-assessor reliability, with most examining healthy adults. Four full-text reports evaluated reliability in people with gait pathologies. The highest reliability indices occurred in the hip and knee in the sagittal plane, with lowest errors in pelvic rotation and obliquity and hip abduction. Lowest reliability and highest error frequently occurred in the hip and knee transverse plane. Methodological quality varied, with key limitations in sample descriptions and strategies for statistical analysis. Reported reliability indices and error magnitudes varied across gait variables and studies. Most studies providing estimates of data error reported values (S.D. or S.E.) of less than 5°, with the exception of hip and knee rotation. Conclusion This review provides evidence that clinically acceptable errors are possible in gait analysis. Variability between studies, however, suggests that they are not always achieved.
Abstract While factor analyses have characterized pace, rhythm and variability as factors that explain variance in gait performance in older adults, comprehensive analyses incorporating many gait parameters have not been undertaken and normative data for many of those parameters are lacking. The purposes of this study were to conduct a factor analysis on nearly two dozen spatiotemporal gait parameters and to contribute to the normative database of gait parameters from healthy, able-bodied men and women over the age of 70. Data were extracted from 294 participants enrolled in the Mayo Clinic Study of Aging. Spatiotemporal gait data were obtained as participants completed two walks across a 5.6-m electronic walkway (GAITRite® ). Five primary domains of spatiotemporal gait performance were identified: a “rhythm” domain was characterized by cadence and temporal parameters such as stride time; a “phase” domain was characterized by temporophasic parameters that constitute distinct divisions of the gait cycle; a “variability” domain encompassed gait cycle and step variability parameters; a “pace” domain was characterized by parameters that included gait speed, step length and stride length; and a “base of support” domain was characterized by step width and step width variability. Several domains differed between men and women and differed across age groups. Reference values of 23 gait parameters are presented which researchers or clinicians can use for assessing and interpreting gait dysfunction in aging persons.
Abstract The determination of gait events such as heel strike and toe-off provide the basis for defining stance and swing phases of gait cycles. Two algorithms for determining event times for treadmill and overground walking based solely on kinematic data are presented. Kinematic data from treadmill walking trials lasting 20–45 s were collected from three subject populations (healthy young, n = 7; multiple sclerosis, n = 7; stroke, n = 4). Overground walking trials consisted of approximately eight successful passes over two force plates for a healthy subject population ( n = 5). Time of heel strike and toe-off were determined using the two new computational techniques and compared to events detected using vertical ground reaction force (GRF) as a gold standard. The two algorithms determined 94% of the treadmill events from healthy subjects within one frame (0.0167 s) of the GRF events. In the impaired populations, 89% of treadmill events were within two frames (0.0334 s) of the GRF events. For overground trials, 98% of events were within two frames. Automatic event detection from the two kinematic-based algorithms will aid researchers by accurately determining gait events during the analysis of treadmill and overground walking.
Abstract Using simulated falls performed under supervised conditions and activities of daily living (ADL) performed by elderly subjects, the ability to discriminate between falls and ADL was investigated using tri-axial accelerometer sensors, mounted on the trunk and thigh. Data analysis was performed using M ATLAB to determine the peak accelerations recorded during eight different types of falls. These included; forward falls, backward falls and lateral falls left and right, performed with legs straight and flexed. Falls detection algorithms were devised using thresholding techniques. Falls could be distinguished from ADL for a total data set from 480 movements. This was accomplished using a single threshold determined by the fall-event data-set, applied to the resultant-magnitude acceleration signal from a tri-axial accelerometer located at the trunk.
Abstract 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.
Abstract Symmetry is a gait characteristic that is increasingly measured and reported, particularly in the stroke patient population. However, there is no accepted standard for assessing symmetry making it difficult to compare across studies and establish criteria to guide clinical decision making. This study compares the most common expressions of spatiotemporal gait symmetry to describe post-stroke gait and makes recommendations regarding the most suitable measure for standardization. The following symmetry equations were compared: symmetry ratio, symmetry index, gait asymmetry and symmetry angle using step length, swing time, stance time, double support time and an intra-limb ratio of swing: stance time. Comparisons were made within a group of 161 community-dwelling, ambulatory individuals with stroke and 81 healthy adults as a reference group. Our analysis supports the recommendations of the symmetry ratio as the equation for standardization and step length, swing time and stance time as the gait parameters to be used in the equation. Future work should focus on establishing the intra-individual variability of these measures and linking them to mechanisms of gait dysfunction.
Highlights ► Gait variability is often used to assess fall risk in elderly subjects. ► Local dynamic stability may be an additional predictor of fall risk. ► Gait kinematics were measured in 134 healthy elderly subjects walking on a treadmill. ► Variability and local dynamic stability were, individually and combined, associated with fall history. ► Increased variability and decreased local dynamic stability are possible risk factors for falling.
Abstract The Gait Deviation Index (GDI) has been proposed as an index of overall gait pathology. This study proposes an interpretation of the difference measure upon which the GDI is based, which naturally leads to the definition of a similar index, the Gait Profile Score (GPS). The GPS can be calculated independently of the feature analysis upon which the GDI is based. Understanding what the underlying difference measure represents also suggests that reporting a raw score, as the GPS does, may have advantages over the logarithmic transformation and z-scaling incorporated in the GDI. It also leads to the concept of a Movement Analysis Profile (MAP) to summarise much of the information contained within kinematic data. A validation study on all children attending a paediatric gait analysis service over 3 years (407 children) provides evidence to support the use of the GPS through analysis of its frequency distribution across different Gross Motor Function Classification System (GMFCS) and Gillette Functional Assessment Questionnaire (FAQ) categories, investigation of intra-session variability, and correlation with the square root of GGI. Correlation with GDI confirms the strong relationship between the two measures. The study concludes that GDI and GPS are alternative and closely related measures. The GDI has prior art and is particularly useful in applications arising out of feature analysis such as cluster analysis or subject matching. The GPS will be easier to calculate for new models where a large reference dataset is not available and in association with applications using the MAP.
Abstract The elderly population is growing rapidly. Fall related injuries are a central problem for this population. Elderly people desire to live at home, and thus, new technologies, such as automated fall detectors, are needed to support their independence and security. The aim of this study was to evaluate different low-complexity fall detection algorithms, using triaxial accelerometers attached at the waist, wrist, and head. The fall data were obtained from standardized types of intentional falls (forward, backward, and lateral) in three middle-aged subjects. Data from activities of daily living were used as reference. Three different detection algorithms with increasing complexity were investigated using two or more of the following phases of a fall event: beginning of the fall, falling velocity, fall impact, and posture after the fall. The results indicated that fall detection using a triaxial accelerometer worn at the waist or head is efficient, even with quite simple threshold-based algorithms, with a sensitivity of 97–98% and specificity of 100%. The most sensitive acceleration parameters in these algorithms appeared to be the resultant signal with no high-pass filtering, and the calculated vertical acceleration. In this study, the wrist did not appear to be an applicable site for fall detection. Since a head worn device includes limitations concerning usability and acceptance, a waist worn accelerometer, using an algorithm that recognizes the impact and the posture after the fall, might be optimal for fall detection.
Abstract Computerized assessment of gait is commonly used in both research and clinical settings to quantify gait mechanics and detect change in performance. Minimal Detectable Change values have only recently been reported, are only available for patient populations, and in many cases exceed 10°. Twenty nine healthy individuals underwent two biomechanical gait assessments separated by 5.6 (SD 2.2) days, with two raters for each session. All subjects walked at a self selected pace and three controlled velocities. ICC, SEM and MDC for kinematic and kinetic measures were calculated for interrater-intrasession, intrarater-intersession and interrater-intersession. ICC values were in the good to excellent range ( r > 0.75) for all kinematic and kinetic variables and all comparisons. MDC values were lower than previously published data for all similar comparisons. The results of the current study suggest that reliability is good to excellent across a range of controlled walking velocities and the introduction of a second rater does not appreciably impact ICC or MDC values. In young healthy adults changes in gait kinematics of greater than approximately 5° can be identified when comparing between sessions.
Highlights • WBB is a low-cost, portable force-plate with trade-offs in measurement uncertainty. • Total uncertainty across WBB's is ±9.1 N for force and ±4.1 mm for CoP. • Repeatability within a single WBB is ±4.5 N for force and ±1.5 mm for CoP. • Wear does not significantly impact the performance of the WBB. • WBB factory calibration values are comparable to empirical calibration values.
Highlights ► Runners can gain more compliance in the lower extremity with a forefoot strike. ► Run barefoot with heel strike pattern may subject to injuries more easily than shod. ► Higher activity in the gastrocnemius was observed when running with a forefoot strike.
Highlights ► Stopwatch-timed mobility tests are insensitive to mild multiple sclerosis (MS). ► We compared timed mobility tests with instrumented body-worn sensors in the clinic. ► Stopwatch timed measures did not distinguish mild MS from control subjects. ► The sensors found significant differences in balance and gait parameters in MS. ► Body-worn sensors may prove a useful and practical MS mobility outcome measure.
Abstract This article describes a new multivariate measure of overall gait pathology called the Gait Deviation Index (GDI). The first step in developing the GDI was to use kinematic data from a large number of walking strides to derive a set of mutually independent joint rotation patterns that efficiently describe gait. These patterns are called gait features . Linear combinations of the first 15 gait features produced a 98% faithful reconstruction of both the data from which they were derived and 1000 validation strides not used in the derivation. The GDI was then defined as a scaled distance between the 15 gait feature scores for a subject and the average of the same 15 gait feature scores for a control group of typically developing (TD) children. Concurrent and face validity data for the GDI are presented through comparisons with the Gillette Gait Index (GGI), Gillette Functional Assessment Questionnaire Walking Scale (FAQ), and topographic classifications within the diagnosis of Cerebral Palsy (CP). The GDI and GGI are strongly correlated ( r2 = 0.56). The GDI scales with FAQ level, distinguishes levels from one another, and is normally distributed across FAQ levels six to ten and among TD children. The GDI also scales with respect to clinical involvement based on topographic CP classification in Hemiplegia Types I–IV, Diplegia, Triplegia and Quadriplegia. The GDI offers an alternative to the GGI as a comprehensive quantitative gait pathology index, and can be readily computed using the electronic addendum provided with this article.