A Kinematic Data-Driven Approach to Differentiate Involuntary Choreic Movements in Individuals With Neurological Conditions.

OBJECTIVE: The ability to differentiate similar choreic involuntary movements could lay the groundwork for the development of a minimally-invasive screening tool for their etiology and provide in-depth understandings of pathophysiology. As a first step, we investigate kinematic differences between Huntington's disease (HD) chorea and Parkinson's disease (PD) choreic levodopa-induced dyskinesia (LID), which have distinct pathological causes yet share a great kinematic resemblance. METHODS: Twenty subjects with HD and ten subjects with PD stood with both upper limbs in front of them for approximately 60 seconds. The three-dimensional velocity time-series of involuntary movements of both hands were segmented into one-dimensional sub-movements abutted by velocity zero-crossings. A combination of unsupervised and supervised machine learning algorithms was employed to automatically select data features extracted from sub-movements and distinguish the two types of involuntary choreic movements. RESULTS: The trained model was able to accurately classify chorea vs. LID with an Area Under the Receiver Operating Characteristic Curve of 99.5%. A set of important features contributing to the construction of the classification model were identified and investigated. CONCLUSION: The trained model may serve as a tool for the automatic identification of different types of involuntary choreic movements, enabling continuous monitoring and personalized treatment for patients in various clinical settings. SIGNIFICANCE: The results provide insights into kinematic characteristics of HD chorea and PD LID, which is the first step towards an improved general understanding of involuntary choreic movements.

How Long Should GPS Recording Lengths Be to Capture the Community Mobility of An Older Clinical Population? A Parkinson's Example.

Wearable global position system (GPS) technology can help those working with older populations and people living with movement disorders monitor and maintain their mobility level. Health research using GPS often employs inconsistent recording lengths due to the lack of a standard minimum GPS recording length for a clinical context. Our work aimed to recommend a GPS recording length for an older clinical population. Over 14 days, 70 older adults with Parkinson's disease wore the wireless inertial motion unit with GPS (WIMU-GPS) during waking hours to capture daily "time outside", "trip count", "hotspots count" and "area size travelled". The longest recording length accounting for weekend and weekdays was ≥7 days of ≥800 daily minutes of data (14 participants with 156, 483.9 min recorded). We compared the error rate generated when using data based on recording lengths shorter than this sample. The smallest percentage errors were observed across all outcomes, except "hotspots count", with daily recordings ≥500 min (8.3 h). Eight recording days will capture mobility variability throughout days of the week. This study adds empirical evidence to the sensor literature on the required minimum duration of GPS recording.

Parkinsonian Symptoms, Not Dyskinesia, Negatively Affect Active Life Participation of Dyskinetic Patients with Parkinson's Disease.

Background: The impact of slight-to-moderate levodopa-induced dyskinesia (LID) on the level of participation in active life in patients with Parkinson's disease (PD) has never been objectively determined. Methods: Levels of LID, tremor and bradykinesia were measured during best-ON state in 121 patients diagnosed with PD and having peak-dose LID using inertial sensors positioned on each body limb. Rigidity and postural instability were assessed using clinical evaluations. Cognition and depression were assessed using the MMSE and the GDS-15. Participation in active life was assessed in patients and in 69 healthy controls using the Activity Card Sort (ACS), which measures levels of activity engagement and activities affected by the symptomatology. Outcome measures were compared between patients and controls using ANCOVA, controlling for age or Wilcoxon-Mann-Whitney tests. Spearman correlations and multivariate analyses were then performed between symptomatology and ACS scores. Results: Patients had significantly lower activity engagement than controls and had significantly affected activities. LID was neither associated with activity engagement nor affected activities. Higher levels of tremor, postural instability, cognitive decline and depression were associated with lower activity engagement and higher affected activities. Multivariate analyses revealed that only tremor, postural instability and depression accounted significantly in the variances of these variables. Discussion: Slight-to-moderate LID had little impact compared to other symptoms on the level of participation in active life, suggesting that other symptoms should remain the treatment priority to maintain the level of participation of patients in an active lifestyle.

Can We Predict the Motor Performance of Patients With Parkinson's Disease Based on Their Symptomatology?

Introduction: Parkinson's disease hinders the ability of a person to perform daily activities. However, the varying impact of specific symptoms and their interactions on a person's motor repertoire is not understood. The current study investigates the possibility to predict global motor disabilities based on the patient symptomatology and medication. Methods: A cohort of 115 patients diagnosed with Parkinson's disease (mean age = 67.0 ± 8.7 years old) participated in the study. Participants performed different tasks, including the Timed-Up & Go, eating soup and the Purdue Pegboard test. Performance on these tasks was judged using timing, number of errors committed, and count achieved. K-means method was used to cluster the overall performance and create different motor performance groups. Symptomatology was objectively assessed for each participant from a combination of wearable inertial sensors (bradykinesia, tremor, dyskinesia) and clinical assessment (rigidity, postural instability). A multinomial regression model was derived to predict the performance cluster membership based on the patients' symptomatology, socio-demographics information and medication. Results: Clustering exposed four distinct performance groups: normal behavior, slightly affected in fine motor tasks, affected only in TUG, and affected in all areas. The statistical model revealed that low to moderate level of dyskinesia increased the likelihood of being in the normal group. A rise in postural instability and rest tremor increase the chance to be affected in TUG. Finally, LEDD did not help distinguishing between groups, but the presence of Amantadine as part of the medication regimen appears to decrease the likelihood of being part of the groups affected in TUG. Conclusion: The approach allowed to demonstrate the potential of using clinical symptoms to predict the impact of Parkinson's disease on a person's mobility performance.

Comparing GPS-Based Community Mobility Measures with Self-report Assessments in Older Adults with Parkinson's Disease.

BACKGROUND: Real-life community mobility (CM) measures for older adults, especially those with Parkinson's disease (PD), are important tools when helping individuals maintain optimal function and quality of life. This is one of the first studies to compare an objective global positioning system (GPS) sensor and subjective self-report CM measures in an older clinical population. METHODS: Over 14 days, 54 people in Ontario, Canada with early to mid-stage PD (mean age = 67.5 ± 6.3 years; 47 men; 46 retired) wore a wireless inertial measurement unit with GPS (WIMU-GPS), and completed the Life Space Assessment and mobility diaries. We assessed the convergent validity, reliability and agreement on mobility outcomes using Spearman's correlation, intraclass correlation coefficient, and Bland-Altman analyses, respectively. RESULTS: Convergent validity was attained by the WIMU-GPS for trip frequency (rs = .69, 95% confidence interval [CI] = 0.52-0.81) and duration outside (rs = .43, 95% CI = 0.18-0.62), but not for life space size (rs = .39, 95% CI = 0.14-0.60). The Life Space Assessment exhibited floor and ceiling effects. Moderate agreements were observed between WIMU-GPS and diary for trip frequency and duration (intraclass correlation coefficients = 0.71, 95% CI = 0.51-0.82; 0.67, 95% CI = 0.42-0.82, respectively). Disagreement was more common among nonretired individuals. CONCLUSIONS: WIMU-GPS could replace diaries for trip frequency and duration assessments in older adults with PD. Both assessments are best used for retired persons. However, the Life Space Assessment may not reflect actual mobility.

Remnants of Cardinal Symptoms of Parkinson's Disease, Not Dyskinesia, Are Problematic for Dyskinetic Patients Performing Activities of Daily Living.

Introduction: The impact of levodopa-induced dyskinesia (LID) on the daily lives of patients with Parkinson's disease (PD) remains to be determined. Furthermore, evidence suggests that cardinal motor symptoms of PD may coexist with LID, but their impact on activities of daily living (ADL) relative to LID is not known. This cross-sectional study aimed at determining the effect of LID and cardinal motor symptoms of PD on ADL in patients who were experiencing peak-dose choreic-type LID. Method: One hundred and twenty-one patients diagnosed with PD known to experience choreic-type LID were recruited for the study. Patients were asked to perform a set of ADL. Levels of LID, tremor, bradykinesia, and freezing of gait (FoG) were measured using 17 inertial sensors design to capture full body movements, while rigidity, and postural instability were assessed using clinical evaluations. Cognition was also assessed using the mini-mental state examination. Success criteria were set for each ADL using the time needed to perform the task and errors measured in 69 age-gender-matched healthy controls. Binary logistic regressions were used to identify symptoms influencing success or failure for each activity. Receiver operating characteristic curves were computed on each significant symptom, and Youden indexes were calculated to determine the critical level of symptomatology at which the performance significantly changed. Results: Results show that 97.7% of patients who presented with LID during the experiment also presented with at least one cardinal motor symptom. On average, patients took more time and did more errors during ADL. Multivariate analyses revealed that for the great majority of ADL, LID were not associated with worsening of performance; however, postural instability, tremor, rigidity, and cognitive decline significantly decreased the odds of success. Conclusions: Residual symptoms of PD, such as tremor, rigidity, and postural instability still present at peak-dose were more problematic than LID in the performance of ADL for patients experiencing slight-to-moderate LID. We also found that cognitive decline was associated with decreased performance in certain tasks. Therefore, a strategy using lower doses of medication to manage LID may be counterproductive since it would not address most of these symptoms already present in patients.

Psychometric properties of home accessibility assessment tools: A systematic review.

BACKGROUND.: Although home environment assessments are commonly performed by occupational therapists working in home care, use of nonstandardized measures created in-house or lack of measure use can cast a shadow over the quality of these assessments for people with disabilities. To ensure quality of home environment assessments, occupational therapists need standardized measures with demonstrated psychometric properties. PURPOSE.: This study provides a critical appraisal of objective accessibility measures of the home environment. METHOD.: A systematic review was undertaken for which three databases-CINAHL, PubMed, and Embase-were searched to identify accessibility measures of the home environment and evaluate their psychometric properties. Two authors independently assessed the quality of selected studies using the critical appraisal form for psychometric articles. FINDINGS.: Ten studies discussing seven accessibility measures were identified and selected for this review. No measures showed strong evidence of both good reliability and validity. Only one study addressed the responsiveness of a measure of accessibility. IMPLICATIONS.: As occupational therapists are specialists of the person-environment relationship, the lack of evidence of the psychometric properties of objective accessibility measures of the home environment harms evidence-based occupational therapy practice. This review identified the most promising assessment tools, but further research is needed.

Parkinson's disease patients experiencing peak-dose dyskinesia redistribute involuntary movements throughout their body to improve motor control.

INTRODUCTION: In Parkinson's disease (PD), dyskinesia is considered a major side effect of dopamine replacement therapy. Nevertheless, many patients with dyskinesia function adequately. OBJECTIVE: To study objectively dyskinesia phenomenology in order to understand why or how patients with dyskinesia are still able to perform motor tasks. METHODS: Patients with and without dyskinesia, as well as healthy older adults, performed a geostationary task during which they attempted to stabilize a glass of water at eye level. Dyskinesia amplitude displayed by each body segment was extracted from accelerometers, and its distribution among the segments, analyzed. RESULTS: Patients experiencing dyskinesia initially distributed most of their dyskinesia away from the segments directly involved in the task. With time, this distribution shifts back towards the hand. CONCLUSION: Our results suggest that patients developed a strategy of involuntary movement's redistribution to attenuate their functional impact on voluntary movements. However, this strategy can only be maintained for a certain period before "re-emerging" dyskinesia occurs.

Quantification of Free-Living Community Mobility in Healthy Older Adults Using Wearable Sensors.

Introduction: Understanding determinants of community mobility disability is critical for developing interventions aimed at preventing or delaying disability in older adults. In an effort to understand these determinants, capturing and measuring community mobility has become a key factor. The objectives of this paper are to present and illustrate the signal processing workflow and outcomes that can be extracted from an activity and community mobility measurement approach based on GPS and accelerometer sensor data and 2) to explore the construct validity of the proposed measurement approach using data collected from healthy older adults in free-living conditions. Methods: Personal, functional impairment and environmental variables were obtained by self-report questionnaires in 75 healthy community-living older adults (mean age = 66 ± 7 years old) living on the island of Montreal, QC, Canada. Participants wore, for 14 days during waking hours on the hip, a data logger incorporating a GPS receiver with a 3-axis accelerometer. Time at home ratio (THR), Trips out (TO), Destinations (D), Maximal distance of destinations (MDD), Active time ratio (ATR), Steps (S), Distance in a vehicle (DV), Time in a vehicle (TV), Distance on foot (DF), Time on foot (TF), Ellipse area (EA), and Ellipse maximum distance (EMD) were extracted from the recordings. Results: After applying quality control criteria, the original data set was reduced from 75 to 54 participants (28% attrition). Results from the remaining sample show that under free-living conditions in healthy older adults, location, activity and community mobility outcomes vary across individuals and certain personal variables (age, income, living situation, professional status, vehicle access) have potential mitigating effects on these outcomes. There was a significant (yet small) relationship (rho < 0.40) between self-reported life space and MDD, DV, EA, and EMD. Conclusion: Wearability and usability of the devices used to capture free-living community mobility impact participant compliance and the quality of the data. The construct validity of the proposed approach appears promising but requires further studies directed at populations with mobility impairments.

Cardinal Motor Features of Parkinson's Disease Coexist with Peak-Dose Choreic-Type Drug-Induced Dyskinesia.

BACKGROUND: Clinical and anecdotal observations propose that patients with Parkinson's disease (PD) may show drug-induced dyskinesia (DID) concomitantly with cardinal motor features. However, the extent of the concomitant presence of DID and cardinal features remains to be determined. OBJECTIVES: This cross-sectional study measured peak-dose choreic-type DID in a quantitative manner in patients diagnosed with PD, and determined whether symptoms such as tremor, bradykinesia, rigidity, postural instability or freezing of gait (FoG) were still detectable in these patients. METHODS: 89 patients diagnosed with PD were recruited and assessed using a combination of quantitative measures using inertial measurement units to capture DID, tremor, bradykinesia, and FoG. Clinical evaluations were also used to assess rigidity and postural instability. Motor symptoms of PD were assessed 3 times during the testing period, and a series of activities of daily living were repeated twice, in between clinical tests, during which the level of DID was quantified. Peak-dose was identified as the period during which patients had the highest levels of DID. Levels of tremor, rigidity, bradykinesia, postural instability, and FoG were used to determine the percentage of patients showing these motor symptoms simultaneously with DID. RESULTS: 72.4% of patients tested presented with measurable DID during the experiment. Rest, postural and kinetic tremor (12.7% , 38.1% , and 15.9% respectively), bradykinesia (28.6% ), rigidity (55.6% ), postural instability (71.4% ) and FoG (9.5% ) were detected simultaneously with DID. CONCLUSIONS: PD symptomatology remains present in patients showing peak-dose choreic-type DID, illustrating the challenge facing physicians when trying to avoid dyskinesia while attempting to alleviate motor symptoms.

Cranio-Caudal Kinematic Turn Signature Assessed with Inertial Systems As a Marker of Mobility Deficits in Parkinson's Disease.

BACKGROUND: Turning is a challenging mobility task requiring proper planning, coordination, and postural stability to be executed efficiently. Turn deficits can impair mobility and lead to falls in patients with neurodegenerative disease, such as Parkinson's disease (PD). It was previously shown that the cranio-caudal sequence involved during a turn (i.e., motion is initiated by the head, followed by the trunk) exhibits a signature that can be captured using an inertial system and analyzed through the Kinematics Theory. The so-called cranio-caudal kinematic turn signature (CCKS) metrics derived from this approach could, therefore, be a promising avenue to develop and track markers to measure early mobility deficits. OBJECTIVE: The current study aims at exploring the discriminative validity and sensitivity of CCKS metrics extracted during turning tasks performed by patients with PD. METHODS: Thirty-one participants (16 asymptomatic older adults (OA): mean age = 69.1 ± 7.5 years old; 15 OA diagnosed with early PD ON and OFF medication, mean age = 65.8 ± 8.4 years old) performed repeated timed up-and-go (TUG) tasks while wearing a portable inertial system. CCKS metrics (maximum head to trunk angle reached and commanded amplitudes of the head to trunk neuromuscular system, estimated from a sigma-lognormal model) were extracted from kinematic data recorded during the turn phase of the TUG tasks. For comparison purposes, common metrics used to analyze the quality of a turn using inertial systems were also calculated over the same trials (i.e., the number of steps required to complete the turn and the turn mean and maximum velocities). RESULTS: All CCKS metrics discriminated between OA and patients (p ≤ 0.041) and were sensitive to change in PD medication state (p ≤ 0.033). Common metrics were also able to discriminate between OA and patients (p < 0.014), but they were unable to capture the change in medication state this early in the disease (p ≥ 0.173). CONCLUSION: The enhanced sensitivity to change of the proposed CCKS metrics suggests a potential use of these metrics for mobility impairments identification and fluctuation assessment, even in the early stages of the disease.

Using Inertial Sensors to Automatically Detect and Segment Activities of Daily Living in People With Parkinson's Disease.

Wearable sensors such as inertial measurement units (IMUs) have been widely used to measure the quantity of physical activities during daily living in healthy and people with movement disorders through activity classification. These sensors have the potential to provide valuable information to evaluate the quality of the movement during the activities of daily living (ADL), such as walking, sitting down, and standing up, which could help clinicians to monitor rehabilitation and pharmaceutical interventions. However, high accuracy in the detection and segmentation of these activities is necessary for proper evaluation of the quality of the performance within a given segment. This paper presents algorithms to process IMU data, to detect and segment unstructured ADL in people with Parkinson's disease (PD) in simulated free-living environment. The proposed method enabled the detection of 1610 events of ADL performed by nine community dwelling older adults with PD under simulated free-living environment with 90% accuracy (sensitivity = 90.8%, specificity = 97.8%) while segmenting these activities within 350 ms of the "gold-standard" manual segmentation. These results demonstrate the robustness of the proposed method to eventually be used to automatically detect and segment ADL in free-living environment in people with PD. This could potentially lead to a more expeditious evaluation of the quality of the movement and administration of proper corrective care for patients who are under physical rehabilitation and pharmaceutical intervention for movement disorders.

Camera pose estimation to improve accuracy and reliability of joint angles assessed with attitude and heading reference systems.

Joint kinematics can be assessed using orientation estimates from Attitude and Heading Reference Systems (AHRS). However, magnetically-perturbed environments affect the accuracy of the estimated orientations. This study investigates, both in controlled and human mobility conditions, a trial calibration technic based on a 2D photograph with a pose estimation algorithm to correct initial difference in AHRS Inertial reference frames and improve joint angle accuracy. In controlled conditions, two AHRS were solidly affixed onto a wooden stick and a series of static and dynamic trials were performed in varying environments. Mean accuracy of relative orientation between the two AHRS was improved from 24.4° to 2.9° using the proposed correction method. In human conditions, AHRS were placed on the shank and the foot of a participant who performed repeated trials of straight walking and walking while turning, varying the level of magnetic perturbation in the starting environment and the walking speed. Mean joint orientation accuracy went from 6.7° to 2.8° using the correction algorithm. The impact of starting environment was also greatly reduced, up to a point where one could consider it as non-significant from a clinical point of view (maximum mean difference went from 8° to 0.6°). The results obtained demonstrate that the proposed method improves significantly the mean accuracy of AHRS joint orientation estimations in magnetically-perturbed environments and can be implemented in post processing of AHRS data collected during biomechanical evaluation of motion.

Capturing the Cranio-Caudal Signature of a Turn with Inertial Measurement Systems: Methods, Parameters Robustness and Reliability.

BACKGROUND: Turning is a challenging mobility task requiring coordination and postural stability. Optimal turning involves a cranio-caudal sequence (i.e., the head initiates the motion, followed by the trunk and the pelvis), which has been shown to be altered in patients with neurodegenerative diseases, such as Parkinson's disease as well as in fallers and frails. Previous studies have suggested that the cranio-caudal sequence exhibits a specific signature corresponding to the adopted turn strategy. Currently, the assessment of cranio-caudal sequence is limited to biomechanical labs which use camera-based systems; however, there is a growing trend to assess human kinematics with wearable sensors, such as attitude and heading reference systems (AHRS), which enable recording of raw inertial signals (acceleration and angular velocity) from which the orientation of the platform is estimated. In order to enhance the comprehension of complex processes, such as turning, signal modeling can be performed. AIM: The current study investigates the use of a kinematic-based model, the sigma-lognormal model, to characterize the turn cranio-caudal signature as assessed with AHRS. METHODS: Sixteen asymptomatic adults (mean age = 69.1 ± 7.5 years old) performed repeated 10-m Timed-Up-and-Go (TUG) with 180° turns, at varying speed. Head and trunk kinematics were assessed with AHRS positioned on each segments. Relative orientation of the head to the trunk was then computed for each trial and relative angular velocity profile was derived for the turn phase. Peak relative angle (variable) and relative velocity profiles modeled using a sigma-lognormal approach (variables: Neuromuscular command amplitudes and timing parameters) were used to extract and characterize the cranio-caudal signature of each individual during the turn phase. RESULTS: The methodology has shown good ability to reconstruct the cranio-caudal signature (signal-to-noise median of 17.7). All variables were robust to speed variations (p > 0.124). Peak relative angle and commanded amplitudes demonstrated moderate to strong reliability (ICC between 0.640 and 0.808). CONCLUSION: The cranio-caudal signature assessed with the sigma-lognormal model appears to be a promising avenue to assess the efficiency of turns.

High Intensity Exercise: Can It Protect You from A Fast Food Diet?

The purpose of this study was to assess the ability of high intensity exercise to counteract the deleterious effects of a fast food diet on the cardiometabolic profile of young healthy men. Fifteen men were subjected to an exclusive fast food diet from a popular fast food restaurant chain (three extra value meals/day + optional snack) for 14 consecutive days. Simultaneously, participants were asked to perform each day high intensity interval training (HIIT) (15 × 60 sec sprint intervals (~90% of maximal heart rate)) on a treadmill. Fast food diet and energy expenditure profiles of the participants during the intervention were assessed as well as body composition (DXA), cardiometabolic profile (lipid, hepatic enzymes, glycated hemoglobin, glucose, insulin, hsC-reactive protein (hsCRP) and blood pressure) and estimated maximal oxygen consumption (VO2 max) pre- and post-experiment. We found significant improvements for fat mass, lean body mass, estimated VO2 max, fasting glucose, serum lipoprotein(a) and hsCRP after the intervention (p < 0.05). HDL-cholesterol significantly decreased (p < 0.002), but the triglycerides/HDL-cholesterol ratio did not change. All other cardiometabolic variables measured remained stable, which includes the primary outcome: the HOMA index (pre: 1.83 ± 1.2 vs. post: 1.54 ± 0.7 values; p = 0.35). In conclusion, in large part, insulin resistance and the cardiometabolic profile of young healthy individuals seems to be protected by HIIT from a fast food diet.

Do Bradykinesia and Tremor Interfere in Voluntary Movement of Essential Tremor Patients? Preliminary Findings.

BACKGROUND: The aim of this study was to determine whether tremor and bradykinesia impacted a dexterous activity performed by patients with essential tremor (ET). METHODS: Core bradykinesia was assessed in 27 controls and 15 patients with ET using a rapid alternating movement (RAM) task. Then, participants performed a "counting money" counting tasks while equipped with inertial measurement units to detect and quantify tremor during movement. The time required to perform subsections of the tasks and the rate of failure (errors) were compared between groups using Mann-Whitney U tests and a chi-square test, respectively. RESULTS: Patients with ET presented with significant bradykinesia during the RAM task and had more tremor during the counting money task. However, the time required to perform the task and rate of failure were similar between groups. DISCUSSION: Results show that even though bradykinesia was detected during fast movements, and that tremor was present during a task requiring dexterity, both symptoms did not interfere with the performance of patients with ET. This pilot study suggests that there may be a threshold at which tremor will become problematic. Determining this threshold for a wide range of daily activities may help determine when it is appropriate to initiate treatment for patients with ET.

Inertial measurement systems for segments and joints kinematics assessment: towards an understanding of the variations in sensors accuracy.

BACKGROUND: Joints kinematics assessment based on inertial measurement systems, which include attitude and heading reference system (AHRS), are quickly gaining in popularity for research and clinical applications. The variety of the tasks and contexts they are used in require a deep understanding of the AHRS accuracy for optimal data interpretation. However, published accuracy studies on AHRS are mostly limited to a single task measured on a limited number of segments and participants. This study assessed AHRS sensors kinematics accuracy at multiple segments and joints through a variety of tasks not only to characterize the system's accuracy in these specific conditions, but also to extrapolate the accuracy results to a broader range of conditions using the characteristics of the movements (i.e. velocity and type of motion). Twenty asymptomatic adults ([Formula: see text] = 49.9) performed multiple 5 m timed up and go. Participants' head, upper trunk, pelvis, thigh, shank and foot were simultaneously tracked using AHRS and an optical motion capture system (gold standard). Each trial was segmented into basic tasks (sit-to-stand, walk, turn). RESULTS: At segment level, results revealed a mean root-mean-squared-difference [Formula: see text] varying between 1.1° and 5.5° according to the segment tracked and the task performed, with a good to excellent agreement between the systems. Relative sensor kinematics accuracy (i.e. joint) varied between 1.6° and 13.6° over the same tasks. On a global scheme, analysis of the effect of velocity on sensor kinematics accuracy showed that AHRS are better adapted to motions performed between 50°/s and 75°/s (roughly thigh and shank while walking). CONCLUSION: Results confirmed that pairing of modules to obtain joint kinematics affects the accuracy compared to segment kinematics. Overall, AHRS are a suitable solution for clinical evaluation of biomechanics under the multi-segment tasks performed although the variation in accuracy should be taken into consideration when judging the clinical meaningfulness of the observed changes.

Auto detection and segmentation of daily living activities during a Timed Up and Go task in people with Parkinson's disease using multiple inertial sensors.

BACKGROUND: Wearable sensors have the potential to provide clinicians with access to motor performance of people with movement disorder as they undergo intervention. However, sensor data often have to be manually classified and segmented before they can be processed into clinical metrics. This process can be time consuming. We recently proposed detection and segmentation algorithms based on peak detection using Inertial Measurement Units (IMUs) to automatically identify and isolate common activities during daily living such as standing up, walking, turning, and sitting down. These algorithms were developed using a homogenous population of healthy older adults. The aim of this study was to investigate the transferability of these algorithms in people with Parkinson's disease (PD). METHODS: A modified Timed Up And Go task was used since it is comprised of these activities, all performed in a continuous fashion. Twelve older adults diagnosed with early PD (Hoehn & Yahr ≤ 2) were recruited for the study and performed three trials of a 10 and 5-m TUG during OFF state. They were outfitted with 17 IMUs covering each body segment. Raw data from IMUs were detrended, normalized and filtered to reveal kinematics peaks that corresponded to different activities. Segmentation was accomplished by identifying the first minimum or maximum to the right and the left of these peaks. Segmentation times were compared to results from two examiners who visually segmented the activities. Specificity and sensitivity were used to evaluate the accuracy of the detection algorithms. RESULTS: Using the same IMUs and algorithms developed in the previous study, we were able to detect these activities with 97.6% sensitivity and 92.7% specificity (n = 432) in PD population. However, with modifications to the IMUs selection, we were able to detect these activities with 100% accuracy. Similarly, applying the same segmentation to PD population, we were able to isolate these activities within ~500 ms of the visual segmentation. Re-optimizing the filtering frequencies, we were able to reduce this difference to ~400 ms. CONCLUSIONS: This study demonstrates the agility and transferability of using a system of IMUs to accurately detect and segment activities in daily living in people with movement disorders.

The Effects of Physical Activity in Parkinson's Disease: A Review.

BACKGROUND: Physical activity (PA) is increasingly advocated as an adjunct intervention for individuals with Parkinson's disease (PD). However, the specific benefits of PA on the wide variety of impairments observed in patients with PD has yet to be clearly identified. OBJECTIVE: Highlight health parameters that are most likely to improve as a result of PA interventions in patients with PD. METHODS: We compiled results obtained from studies examining a PA intervention in patients with PD and who provided statistical analyses of their results. 868 outcome measures were extracted from 106 papers published from 1981 to 2015. The results were classified as having a statistically significant positive effect or no effect. Then, outcome measures were grouped into four main categories and further divided into sub-categories. RESULTS: Our review shows that PA seems most effective in improving Physical capacities and Physical and cognitive functional capacities. On the other hand, PA seems less efficient at improving Clinical symptoms of PD and Psychosocial aspects of life, with only 50% or less of results reporting positive effects. The impact of PA on Cognitive functions and Depression also appears weaker, but few studies have examined these outcomes. DISCUSSION: Our results indicate that PA interventions have a positive impact on physical capacities and functional capacities. However, the effect of PA on symptoms of the disease and psychosocial aspects of life are moderate and show more variability. This review also highlights the need for more research on the effects of PA on cognitive functions, depression as well as specific symptoms of PD.

Subthalamic deep brain stimulation and dopaminergic medication in Parkinson's disease: Impact on inter-limb coupling.

Patients with Parkinson's disease (PD) often present with bimanual coordination deficits whose exact origins remain unclear. One aspect of bimanual coordination is inter-limb coupling. This is characterized by the harmonization of movement parameters between limbs. We assessed different aspects of bimanual coordination in patients with PD, including inter-limb coupling, and determined whether they are altered by subthalamic (STN) deep brain stimulation (DBS) or dopaminergic medication. Twenty PD patients were tested before STN DBS surgery; with and without medication. Post- surgery, patients were tested with their stimulators on and off as well as with and without medication. Patients were asked to perform a unimanual and bimanual rapid repetitive diadochokinesis task. The difference in mean amplitude and mean duration of cycles between hands was computed in order to assess inter-limb coupling. Also, mean angular velocity of both hands and structural coupling were computed for the bimanual task. There was a positive effect of medication and stimulation on mean angular velocity, which relates to clinical improvement. PD patients exhibited temporal inter-limb coupling that was not altered by either medication or STN stimulation. However, PD patients did not exhibit spatial inter-limb coupling. Again, this was not altered by medication or stimulation. Collectively, the results suggest that structures independent of the dopaminergic system and basal ganglia may mediate temporal and spatial inter-limb coupling.