Quantification of upper body movements during gait in older adults and in those with Parkinson's disease: impact of acceleration realignment methodologies

Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson's Disease

Quantitative mobility analysis using wearable sensors, while promising as a diagnostic tool for Parkinson's disease (PD), is not commonly applied in clinical settings. Major obstacles include uncertainty regarding the best protocol for instrumented mobility testing and subsequent data processing, as well as the added workload and complexity of this multi-step process. To simplify sensor-based mobility testing in diagnosing PD, we analyzed data from 262 PD participants and 50 controls performing several motor tasks wearing a sensor on their lower back containing a triaxial accelerometer and a triaxial gyroscope. Using ensembles of heterogeneous machine learning models incorporating a range of classifiers trained on a set of sensor features, we show that our models effectively differentiate between participants with PD and controls, both for mixed-stage PD (92.6% accuracy) and a group selected for mild PD only (89.4% accuracy). Omitting algorithmic segmentation of complex mobility tasks decreased the diagnostic accuracy of our models, as did the inclusion of kinesiological features. Feature importance analysis revealed that Timed Up and Go (TUG) tasks to contribute the highest-yield predictive features, with only minor decreases in accuracy for models based on cognitive TUG as a single mobility task. Our machine learning approach facilitates major simplification of instrumented mobility testing without compromising predictive performance.

Sensitivity to gait improvement after levodopa intake in Parkinson's disease: A comparison study among synthetic kinematic indices

The synthetic indices are widely used to describe balance and stability during gait. Some of these are employed to describe the gait features in Parkinson's disease (PD). However, the results are sometimes inconsistent, and the same indices are rarely used to compare the individuals affected by PD before and after levodopa intake (OFF and ON condition, respectively). Our aim was to investigate which synthetic measure among Harmonic Ratio, Jerk Ratio, Golden Ratio and Trunk Displacement Index is representative of gait stability and harmony, and which of these are more sensitive to the variations between OFF and ON condition. We found that all indices, except the Jerk Ratio, significantly improve after levodopa. Only the improvement of the Trunk Displacement Index showed a direct correlation with the motor improvement measured through the clinical scale UPDRS-III (Unified Parkinson's Disease Rating Scale-part III). In conclusion, we suggest that the synthetic indices can be useful to detect motor changes induced by, but not all of them clearly correlate with the clinical changes achieved with the levodopa administration. In our analysis, only the Trunk Displacement Index was able to show a clear relationship with the PD clinical motor improvement.

Changes in Trunk Variability and Stability of Gait in Patients with Chronic Low Back Pain: Impact of Laboratory versus Daily-Living Environments

BACKGROUND

Individuals with chronic low back pain (CLBP) experience changes in gait control due to pain and/or fear. Although CLBP patients' gait has been performed in laboratory environments, changes in gait control as an adaptation to unstructured daily living environments may be more pronounced than the corresponding changes in laboratory environments. We investigated the impacts of the environment and pathology on the trunk variability and stability of gait in CLBP patients.

METHODS

CLBP patients (n=20) and healthy controls with no low-back pain history (n=20) were tasked with walking in a laboratory or daily-living environment while wearing an accelerometer on the low back. We calculated the stride-to-stride standard deviation and multiscale sample entropy as indices of "gait variability" and the maximum Lyapunov exponent as an index of "gait stability" in both the anterior-posterior and medial-lateral directions. The participants were assessed on the numerical rating scale for pain intensity, the Tampa Scale for Kinesiophobia, and the Roland-Morris Disability Questionnaire for quality of life (QOL).

RESULTS

In a repeated-measures ANOVA, the standard deviation was affected by environment in the anterior-posterior direction and by group and environment in the medial-lateral direction. Multiscale sample entropy showed no effect in the anterior-posterior direction and showed both effects in the medial-lateral direction. Maximum Lyapunov exponents showed both effects in the anterior-posterior direction, but none in the medial-lateral direction. These changes of trunk motor control by CLBP patients were found to be related to pain intensity, fear of movement, and/or QOL in the daily-living environment but not in the laboratory environment.

CONCLUSION

These results revealed that CLBP patients exhibit changes in trunk variability and stability of gait depending on the environment, and they demonstrated that these changes are related to pain, fear, and QOL. We propose useful accelerometer-based assessments of qualitative gait in CLBP patients' daily lives, as it would provide information not available in a general practice setting.

Three-dimensional thoracic and pelvic kinematics and arm swing maximum velocity in older adults using inertial sensor system

Understanding characteristics of torso motion and arm swing of older adults is important. A comprehensive database of three-dimensional thoracic and pelvic kinematics and arm swing maximum velocity of older adults during overground walking is still lacking. Moreover, the relationships between these variables are not fully understood. Therefore, we investigated age and gender effects of three-dimensional thoracic and pelvic ranges of motion and arm swing maximum velocity in 113 healthy old adults (aged 60–89 years) in a 2-min walk test using APDM Movement Monitoring inertial sensor system by two-way ANOVA, and post hoc Bonferroni correction was applied for multiple comparisons between age groups. A paired t-test was used to study the side preference of arm swing maximum velocity. The relationships between variables were investigated via multiple linear regression models. In general, thoracic and pelvic motions showed reduced amplitude with aging. Gait speed, pelvis coronal plane motion and arm swing maximum velocity significantly declined with age. Only the pelvic sagittal plane motion showed a gender main effect. Coronal plane motions of the thorax and pelvis were closely associated, as were sagittal plane motions. Thoracic coronal plane motion was the significant variable influencing pelvic transverse plane motion and vice versa. Gait speed, pelvic coronal and transverse plane motions and thorax sagittal plane motion were significant independent variables that influenced dominant arm maximum velocity. A larger maximum velocity was seen in the left arm. This investigation is valuable for better understanding of gait phenomena and will contribute to identification of gait dysfunction and development of rehabilitation measures.

Validation of a portable system for spatial-temporal gait parameters based on a single inertial measurement unit and a mobile application

There is a lack of commercially available low-cost technologies to assess gait clinically in non-controlled environments. As a consequence of this, there has been poor massification of motion measurement technologies that are both objective and reliable in nature. Advances about the study of gait and its interpretation in recent years using inertial sensors have allowed proposing acceptable alternatives for the development of portable and low-cost systems that contribute to people’s health in places and institutions that cannot acquire or maintain the operation of commercially available systems. A system based on a custom single Inertial Measurement Unit and a mobile application is proposed. Thus, an investigation is carried out using methodologies and algorithms found in the literature in order to get the main gait events and the spatial-temporal gait parameters. Twenty healthy Chilean subjects were assessed using a motion capture system simultaneously with the proposed tool. The results show that it is possible to estimate temporal gait parameters with slight differences respect gold--standard. We reach maximum mean differences of -2.35±5.02[step/min] for cadence, 0.03±0.04[sec] for stride time,0.02±0.03[sec] for step time, ±0.02[sec] for a single support time, 0.01±0.02[sec] for double support time and 0.01±0.03[m] for step length. As a result of experimental findings, we propose a new technological tool that can perform gait analysis. Our proposed system is user-friendly, low-cost, and portable. Therefore, we suggest that it could be an attractive technological tool that healthcare professionals could harness to objectively measure gait in environments that are either within the community or controlled. We also suggest that the tool could be used in countries where advanced clinical tools cannot be acquired. Therefore, we propose in this paper that our system is an attractive, alternative system that can be used for gait analysis by health professionals worldwide.

Validation of a portable system for spatial-temporal gait parameters based on a single inertial measurement unit and a mobile application

There is a lack of commercially available low-cost technologies to assess gait clinically in non-controlled environments. As a consequence of this, there has been poor massification of motion measurement technologies that are both objective and reliable in nature. Advances about the study of gait and its interpretation in recent years using inertial sensors have allowed proposing acceptable alternatives for the development of portable and low-cost systems that contribute to people’s health in places and institutions that cannot acquire or maintain the operation of commercially available systems. A system based on a custom single Inertial Measurement Unit and a mobile application is proposed. Thus, an investigation is carried out using methodologies and algorithms found in the literature in order to get the main gait events and the spatial-temporal gait parameters. Twenty healthy Chilean subjects were assessed using a motion capture system simultaneously with the proposed tool. The results show that it is possible to estimate temporal gait parameters with slight differences respect gold--standard. We reach maximum mean differences of -2.35±5.02[step/min] for cadence, 0.03±0.04[sec] for stride time,0.02±0.03[sec] for step time, ±0.02[sec] for a single support time, 0.01±0.02[sec] for double support time and 0.01±0.03[m] for step length. As a result of experimental findings, we propose a new technological tool that can perform gait analysis. Our proposed system is user-friendly, low-cost, and portable. Therefore, we suggest that it could be an attractive technological tool that healthcare professionals could harness to objectively measure gait in environments that are either within the community or controlled. We also suggest that the tool could be used in countries where advanced clinical tools cannot be acquired. Therefore, we propose in this paper that our system is an attractive, alternative system that can be used for gait analysis by health professionals worldwide.

Wearable Inertial Sensors to Assess Gait during the 6-Minute Walk Test: A Systematic Review

Wearable sensors are becoming increasingly popular for complementing classical clinical assessments of gait deficits. The aim of this review is to examine the existing knowledge by systematically reviewing a large number of papers focusing on the use of wearable inertial sensors for the assessment of gait during the 6-minute walk test (6MWT), a widely recognized, simple, non-invasive, low-cost and reproducible exercise test. After a systematic search on PubMed and Scopus databases, two raters evaluated the quality of 28 full-text articles. Then, the available knowledge was summarized regarding study design, subjects enrolled (number of patients and pathological condition, if any, age, male/female ratio), sensor characteristics (type, number, sampling frequency, range) and body placement, 6MWT protocol and extracted parameters. Results were critically discussed to suggest future directions for the use of inertial sensor devices in the clinics.

Gait Asymmetry Post-Stroke: Determining Valid and Reliable Methods Using a Single Accelerometer Located on the Trunk

Asymmetry is a cardinal symptom of gait post-stroke that is targeted during rehabilitation. Technological developments have allowed accelerometers to be a feasible tool to provide digital gait variables. Many acceleration-derived variables are proposed to measure gait asymmetry. Despite a need for accurate calculation, no consensus exists for what is the most valid and reliable variable. Using an instrumented walkway (GaitRite) as the reference standard, this study compared the validity and reliability of multiple acceleration-derived asymmetry variables. Twenty-five post-stroke participants performed repeated walks over GaitRite whilst wearing a tri-axial accelerometer (Axivity AX3) on their lower back, on two occasions, one week apart. Harmonic ratio, autocorrelation, gait symmetry index, phase plots, acceleration, and jerk root mean square were calculated from the acceleration signals. Test-retest reliability was calculated, and concurrent validity was estimated by comparison with GaitRite. The strongest concurrent validity was obtained from step regularity from the vertical signal, which also recorded excellent test-retest reliability (Spearman's rank correlation coefficients (rho) = 0.87 and Intraclass correlation coefficient (ICC21) = 0.98, respectively). Future research should test the responsiveness of this and other step asymmetry variables to quantify change during recovery and the effect of rehabilitative interventions for consideration as digital biomarkers to quantify gait asymmetry.

Development of a Data Logger for Capturing Human-Machine Interaction in Wheelchair Head-Foot Steering Sensor System in Dyskinetic Cerebral Palsy

The use of data logging systems for capturing wheelchair and user behavior has increased rapidly over the past few years. Wheelchairs ensure more independent mobility and better quality of life for people with motor disabilities. Especially, for people with complex movement disorders, such as dyskinetic cerebral palsy (DCP) who lack the ability to walk or to handle objects, wheelchairs offer a means of integration into daily life. The mobility of DCP patients is based on a head-foot wheelchair steering system. In this work, a data logging system is proposed to capture data from human-wheelchair interaction for the head-foot steering system. Additionally, the data logger provides an interface to multiple Inertial Measurement Units (IMUs) placed on the body of the wheelchair user. The system provides accurate and real-time information from head-foot navigation system pressure sensors on the wheelchair during driving. This system was used as a tool to obtain further insights into wheelchair control and steering behavior of people diagnosed with DCP in comparison with a healthy subject.

Upper body accelerations as a biomarker of gait impairment in the early stages of Parkinson's disease

BACKGROUND

Changes in upper body (UB) motion during gait may be a marker of incipient pathology, intervention response and disease progression in Parkinson's disease (PD), which if independent from the lower body motion, might provide an improved assessment of gait.

RESEARCH QUESTION

This study aimed to test this hypothesis and establish whether variables calculated from accelerations measured on the UB are unique from spatiotemporal characteristics and can contribute to an improved classification of PD gait.

METHODS

Data was obtained from 70 people with PD (69.2 ± 9.9 y.o.

, UPDRS III

36.9 ± 12.3) and 64 age-matched controls (71.6 ± 6.8 y.o.). Spatiotemporal characteristics were measured using a pressure sensitive mat (GAITRite). Head and pelvis accelerations were synchronously measured with wearable inertial sensors (Opal, APDM). Pearson's product-moment correlations were calculated between 49 selected variables from UB accelerations (representing magnitude, smoothness, regularity, symmetry and attenuation) and 16 traditional spatiotemporal characteristics (representing pace, variability, rhythm, asymmetry and postural control). Univariate and multivariate regression analysis was used to test the variables ability to classify PD gait.

RESULTS

The variables were mostly unique from each other (67% of variables recorded an r < 0.3). Univariate and multivariate analysis showed that UB variables were moderately better at classifying PD gait than the spatiotemporal characteristics (Univariate: 0.70 to 0.81, Multivariate: 0.88 to 0.91 AUC).

SIGNIFICANCE

This study showed for the first time that, if aiming at objective and optimal sensitive biomarkers for PD, UB variables should be measured in conjunction with spatiotemporal characteristics to obtain a more holistic assessment of PD gait for use in a clinical or free-living environment.

Free-living and laboratory gait characteristics in patients with multiple sclerosis

Background

Wearable sensors offer the potential to bring new knowledge to inform interventions in patients affected by multiple sclerosis (MS) by thoroughly quantifying gait characteristics and gait deficits from prolonged daily living measurements. The aim of this study was to characterise gait in both laboratory and daily life conditions for a group of patients with moderate to severe ambulatory impairment due to MS. To this purpose, algorithms to detect and characterise gait from wearable inertial sensors data were also validated.

Methods

Fourteen patients with MS were divided into two groups according to their disability level (EDSS 6.5–6.0 and EDSS 5.5–5.0, respectively). They performed both intermittent and continuous walking bouts (WBs) in a gait laboratory wearing waist and shank mounted inertial sensors. An algorithm (W-CWT) to estimate gait events and temporal parameters (mean and variability values) using data recorded from the waist mounted sensor (Dynaport, Mc Roberts) was tested against a reference algorithm (S-REF) based on the shank-worn sensors (OPAL, APDM). Subsequently, the accuracy of another algorithm (W-PAM) to detect and classify WBs was also tested. The validated algorithms were then used to quantify gait characteristics during short (sWB, 5–50 steps), intermediate (iWB, 51–100 steps) and long (lWB, >100 steps) daily living WBs and laboratory walking. Group means were compared using a two-way ANOVA.

Results

W-CWT compared to S-REF showed good gait event accuracy (0.05–0.10 s absolute error) and was not influenced by disability level. It slightly overestimated stride time in intermittent walking (0.012 s) and overestimated highly variability of temporal parameters in both intermittent (17.5%–58.2%) and continuous walking (11.2%–76.7%). The accuracy of W-PAM was speed-dependent and decreased with increasing disability. The ANOVA analysis showed that patients walked at a slower pace in daily living than in the laboratory. In daily living gait, all mean temporal parameters decreased as the WB duration increased. In the sWB, the patients with a lower disability score showed, on average, lower values of the temporal parameters. Variability decreased as the WB duration increased.

Conclusions

This study validated a method to quantify walking in real life in people with MS and showed how gait characteristics estimated from short walking bouts during daily living may be the most informative to quantify level of disability and effects of interventions in patients moderately affected by MS. The study provides a robust approach for the quantification of recognised clinically relevant outcomes and an innovative perspective in the study of real life walking.

Measurement of Axial Rigidity and Postural Instability Using Wearable Sensors

Axial Bradykinesia is an important feature of advanced Parkinson's disease (PD). The purpose of this study is to quantify axial bradykinesia using wearable sensors with the long-term aim of quantifying these movements, while the subject performs routine domestic activities. We measured back movements during common daily activities such as pouring, pointing, walking straight and walking around a chair with a test system engaging a minimal number of Inertial Measurement (IM) based wearable sensors. Participants included controls and PD patients whose rotation and flexion of the back was captured by the time delay between motion signals from sensors attached to the upper and lower back. PD subjects could be distinguished from controls using only two sensors. These findings suggest that a small number of sensors and similar analyses could distinguish between variations in bradykinesia in subjects with measurements performed outside of the laboratory. The subjects could engage in routine activities leading to progressive assessments of therapeutic outcomes.

UPPER BODY ACCELERATIONS DURING LOCOMOTION IN DIFFERENT AGE GROUPS AND GENDERS

Aim: The purpose of this study is to measure the acceleration of upper body (pelvis, shoulder and head) during walking and to investigate whether the acceleration patterns differ among age groups and genders. Methods: Twenty-nine old subjects and thirty young subjects participated in this study. Tri-axial accelerations were measured on the back of upper body (head, shoulder and pelvis). Subjects performed two trials of walking on a treadmill in their own comfortable speeds. Three-way ANOVA (repeated measures) was carried out for the root mean square of each directional acceleration with age, gender and sensor position as independent factors. Results: Age effect was significant on the RMS accelerations of the transverse plane. In the anteroposterior direction, the pelvis acceleration was greater in the younger group, while the head acceleration was greater in the older group ([Formula: see text]). In the mediolateral direction, the pelvis acceleration was comparable between age groups but the shoulder and head accelerations were greater in the older group ([Formula: see text]). The overall accelerations were greater in men than in women ([Formula: see text]). The phase-delay and attenuation of shoulder acceleration relative to the pelvis acceleration was smaller for the elderly in AP and ML directions ([Formula: see text]). Normalization of RMS accelerations by height, weight and leg length did not affect the age differences but negated the gender differences. Discussion: Greater head acceleration in older subjects were related to less attenuation of acceleration in the upper body, which may affect the sensory systems in the head and deteriorate balance control during locomotion.

GaitKeeper: A System for Measuring Canine Gait

It is understood gait has the potential to be used as a window into neurodegenerative disorders, identify markers of subclinical pathology, inform diagnostic algorithms of disease progression and measure the efficacy of interventions. Dogs’ gaits are frequently assessed in a veterinary setting to detect signs of lameness. Despite this, a reliable, affordable and objective method to assess lameness in dogs is lacking. Most described canine lameness assessments are subjective, unvalidated and at high risk of bias. This means reliable, early detection of canine gait abnormalities is challenging, which may have detrimental implications for dogs’ welfare. In this paper, we draw from approaches and technologies used in human movement science and describe a system for objectively measuring temporal gait characteristics in dogs (step-time, swing-time, stance-time). Asymmetries and variabilities in these characteristics are of known clinical significance when assessing lameness but presently may only be assessed on coarse scales or under highly instrumented environments. The system consists an inertial measurement unit, containing a 3-axis accelerometer and gyroscope coupled with a standardized walking course. The measurement unit is attached to each leg of the dog under assessment before it is walked around the course. The data by the measurement unit is then processed to identify steps and subsequently, micro-gait characteristics. This method has been tested on a cohort of 19 healthy dogs of various breeds ranging in height from 34.2 cm to 84.9 cm. We report the system as capable of making precise step delineations with detections of initial and final contact times of foot-to-floor to a mean precision of 0.011 s and 0.048 s, respectively. Results are based on analysis of 12,678 foot falls and we report a sensitivity, positive predictive value and F-score of 0.81, 0.83 and 0.82 respectively. To investigate the effect of gait on system performance, the approach was tested in both walking and trotting with no significant performance deviation with 7249 steps reported for a walking gait and 4977 for a trotting gait. The number of steps reported for each leg were approximately equal and this consistency was true in both walking and trotting gaits. In the walking gait 1965, 1790, 1726 and 1768 steps were reported for the front left, front right, hind left and hind right legs respectively. 1361, 1250, 1176 and 1190 steps were reported for each of the four legs in the trotting gait. The proposed system is a pragmatic and precise solution for obtaining objective measurements of canine gait. With further development, it promises potential for a wide range of applications in both research and clinical practice.