Innovative Detection and Segmentation of Mobility Activities in Patients Living with Parkinson's Disease Using a Single Ankle-Positioned Smartwatch.

BACKGROUND: The automatic detection of activities of daily living (ADL) is necessary to improve long-term home-based monitoring of Parkinson's disease (PD) symptoms. While most body-worn sensor algorithms for ADL detection were developed using laboratory research systems covering full-body kinematics, it is now crucial to achieve ADL detection using a single body-worn sensor that remains commercially available and affordable for ecological use. AIM: to detect and segment Walking, Turning, Sitting-down, and Standing-up activities of patients with PD using a Smartwatch positioned at the ankle. METHOD: Twenty-two patients living with PD performed a Timed Up and Go (TUG) task three times before engaging in cleaning ADL in a simulated free-living environment during a 3 min trial. Accelerations and angular velocities of the right or left ankle were recorded in three dimensions using a Smartwatch. The TUG task was used to develop detection algorithms for Walking, Turning, Sitting-down, and Standing-up, while the 3 min trial in the free-living environment was used to test and validate these algorithms. Sensitivity, specificity, and F-scores were calculated based on a manual segmentation of ADL. RESULTS: Sensitivity, specificity, and F-scores were 96.5%, 94.7%, and 96.0% for Walking; 90.0%, 93.6%, and 91.7% for Turning; 57.5%, 70.5%, and 52.3% for Sitting-down; and 57.5%, 72.9%, and 54.1% for Standing-up. The median of time difference between the manual and automatic segmentation was 1.31 s for Walking, 0.71 s for Turning, 2.75 s for Sitting-down, and 2.35 s for Standing-up. CONCLUSION: The results of this study demonstrate that segmenting ADL to characterize the mobility of people with PD based on a single Smartwatch can be comparable to manual segmentation while requiring significantly less time. While Walking and Turning were well detected, Sitting-down and Standing-up will require further investigation to develop better algorithms. Nonetheless, these achievements increase the odds of success in implementing wearable technologies for PD monitoring in ecological environments.

Instrumented Pre-Hospital Care Simulation Mannequin for Use in Spinal Motion Restrictions Scenarios: Validation of Cervical and Lumbar Motion Assessment.

BACKGROUND: A mid-fidelity simulation mannequin, equipped with an instrumented cervical and lumbar spine, was developed to investigate best practices and train healthcare professionals in applying spinal motion restrictions (SMRs) during the early mobilization and transfer of accident victims with suspected spine injury. The study objectives are to (1) examine accuracy of the cervical and lumbar motions measured with the mannequin; and (2) confirm that the speed of motion has no bearing on this accuracy. METHODS: Accuracy was evaluated by concurrently comparing the orientation data obtained with the mannequin with that from an optoelectronic system. The mannequin's head and pelvis were moved in all anatomical planes of motion at different speeds. RESULTS: Accuracy, assessed by root-mean-square error, varied between 0.7° and 1.5° in all anatomical planes of motion. Bland-Altman analysis revealed a bias ranging from -0.7° to 0.6°, with the absolute limit of agreement remaining below 3.5°. The minimal detectable change varied between 1.3° and 2.6°. Motion speed demonstrated no impact on accuracy. CONCLUSIONS: The results of this validation study confirm the mannequin's potential to provide accurate measurements of cervical and lumbar motion during simulation scenarios for training and research on the application of SMR.

Comparison of Three Motion Capture-Based Algorithms for Spatiotemporal Gait Characteristics: How Do Algorithms Affect Accuracy and Precision of Clinical Outcomes?

Gait assessment is of interest to clinicians and researchers because it provides information about patients' functional mobility. Optoelectronic camera-based systems with gait event detection algorithms are considered the gold standard for gait assessment. Yet, the choice of the algorithm used to process data and extract the desired parameters from those detected gait events has an impact on the validity and reliability of the gait parameters computed. There are multiple techniques documented in the literature for computing gait events, including the analysis of the minimal position of the heel and toe markers, the computation of the relative distance between sacrum and foot markers, and the assessment of the smallest distance between the heel and toe markers. Validation studies conducted on these algorithms report variations in accuracy. Yet, these studies were conducted in different conditions, at varying gait velocities, and on different populations. The purpose of this study is to compare accuracy, precision, and robustness of three algorithms using motion capture data obtained from 25 healthy persons and 21 psoriatic arthritic patients walking at three distinct speeds on an instrumented treadmill. Errors in gait events recognition (heel strike-HS and toe-off-TO) and their impact on gait metrics (stance phase and stride length) are reported and compared to ground reaction force events measured with force plates. Over the 9114 collected steps across all walking speeds, more than 99% of gait events were recognized by all algorithms. On average, HS events were detected within 1.2 ms of the reference for two algorithms, while the third one detected HS late, with an average detection error of 40.7 ms. Yet, significant variations in accuracy were noted with gait speed; the performance decreased for all algorithms at slow speed. TO events were identified early by all algorithms, with an average error ranging from 16.0 to 100.0 ms. These gait events errors lead to 2-15% inaccuracies in stance phase assessment, while the impact on stride length remains below 0.3 cm. Overall, the algorithm based on the relative distance between the sacral and foot markers stood out for its accuracy, precision, and robustness at all walking speeds.

Evaluation of Various State of the Art Head Pose Estimation Algorithms for Clinical Scenarios.

Head pose assessment can reveal important clinical information on human motor control. Quantitative assessment have the potential to objectively evaluate head pose and movements' specifics, in order to monitor the progression of a disease or the effectiveness of a treatment. Optoelectronic camera-based motion-capture systems, recognized as a gold standard in clinical biomechanics, have been proposed for head pose estimation. However, these systems require markers to be positioned on the person's face which is impractical for everyday clinical practice. Furthermore, the limited access to this type of equipment and the emerging trend to assess mobility in natural environments support the development of algorithms capable of estimating head orientation using off-the-shelf sensors, such as RGB cameras. Although artificial vision is a popular field of research, limited validation of human pose estimation based on image recognition suitable for clinical applications has been performed. This paper first provides a brief review of available head pose estimation algorithms in the literature. Current state-of-the-art head pose algorithms designed to capture the facial geometry from videos, OpenFace 2.0, MediaPipe and 3DDFA_V2, are then further evaluated and compared. Accuracy is assessed by comparing both approaches to a baseline, measured with an optoelectronic camera-based motion-capture system. Results reveal a mean error lower or equal to 5.6∘ for 3DDFA_V2 depending on the plane of movement, while the mean error reaches 14.1∘ and 11.0∘ for OpenFace 2.0 and MediaPipe, respectively. This demonstrates the superiority of the 3DDFA_V2 algorithm in estimating head pose, in different directions of motion, and suggests that this algorithm can be used in clinical scenarios.

The Accuracy and Precision of Gait Spatio-Temporal Parameters Extracted from an Instrumented Sock during Treadmill and Overground Walking in Healthy Subjects and Patients with a Foot Impairment Secondary to Psoriatic Arthritis.

The objectives of this study were to assess the accuracy and precision of a system combining an IMU-instrumented sock and a validated algorithm for the estimation of the spatio-temporal parameters of gait. A total of 25 healthy participants (HP) and 21 patients with foot impairments secondary to psoriatic arthritis (PsA) performed treadmill walking at three different speeds and overground walking at a comfortable speed. HP performed the assessment over two sessions. The proposed system's estimations of cadence (CAD), gait cycle duration (GCD), gait speed (GS), and stride length (SL) obtained for treadmill walking were validated versus those estimated with a motion capture system. The system was also compared with a well-established multi-IMU-based system for treadmill and overground walking. The results showed a good agreement between the motion capture system and the IMU-instrumented sock in estimating the spatio-temporal parameters during the treadmill walking at normal and fast speeds for both HP and PsA participants. The accuracy of GS and SL obtained from the IMU-instrumented sock was better compared to the established multi-IMU-based system in both groups. The precision (inter-session reliability) of the gait parameter estimations obtained from the IMU-instrumented sock was good to excellent for overground walking and treadmill walking at fast speeds, but moderate-to-good for slow and normal treadmill walking. The proposed IMU-instrumented sock offers a novel form factor addressing the wearability issues of IMUs and could potentially be used to measure spatio-temporal parameters under clinical conditions and free-living conditions.

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.

Trueness and Minimal Detectable Change of Smartphone Inclinometer Measurements of Shoulder Range of Motion.

BACKGROUND: Digital inclinometer applications using data from embedded sensors on smartphone/multi-purpose pocket computers or "smart digital inclinometers" (SDIs) are now used to clinically assess range of motion (ROM). OBJECTIVES: The objectives of this study were to assess, compared with a biomechanical gold standard (GS), the trueness and minimal detectable change (MDC) of shoulder range of motion (SROM) measurements obtained from an SDI. METHODS: Twenty-five (n = 25) asymptomatic healthy participants performed three trials of shoulder flexion (SF), shoulder abduction (SA), and shoulder external rotation (SER) at full-range and mid-range. MAIN OUTCOME MEASURES: SROM was measured concurrently from sensor data (pitch, yaw, roll angles) from an iPod Touch installed on the posterior aspect of the humerus and 3D orientation of the upper arm obtained from an optical motion tracking system GS. RESULTS: The mean level of bias between SDI and the GS across all SROM measurements was 3.4°, with a 95% confidence interval varying between -8.9° and 15.8°. The mean and standard deviation absolute difference of SDI measurements with the GS were 5.8° ± 3.7° for SF, 8.7° ± 5.2° for SA, and 1.7° ± 1.4° for SER. The trueness of these values varied according to the movement. MDC was 1.9° for SF, 2° for SA, and 0.3° for SER. CONCLUSIONS: SROM measures in SER with an SDI seem to be accurate and robust for clinical use. However, SROM measures in other planes of motion should be interpreted with caution depending on the evaluation objective, the plane of motion assessed, and the range of ROM measured.

Autonomous Quality Control of Joint Orientation Measured with Inertial Sensors.

Clinical mobility assessment is traditionally performed in laboratories using complex and expensive equipment. The low accessibility to such equipment, combined with the emerging trend to assess mobility in a free-living environment, creates a need for body-worn sensors (e.g., inertial measurement units-IMUs) that are capable of measuring the complexity in motor performance using meaningful measurements, such as joint orientation. However, accuracy of joint orientation estimates using IMUs may be affected by environment, the joint tracked, type of motion performed and velocity. This study investigates a quality control (QC) process to assess the quality of orientation data based on features extracted from the raw inertial sensors' signals. Joint orientation (trunk, hip, knee, ankle) of twenty participants was acquired by an optical motion capture system and IMUs during a variety of tasks (sit, sit-to-stand transition, walking, turning) performed under varying conditions (speed, environment). An artificial neural network was used to classify good and bad sequences of joint orientation with a sensitivity and a specificity above 83%. This study confirms the possibility to perform QC on IMU joint orientation data based on raw signal features. This innovative QC approach may be of particular interest in a big data context, such as for remote-monitoring of patients' mobility.

Cervical Spine Motion during Transfer and Stabilization Techniques.

Abstract Objectives. To compare paramedics' ability to minimize cervical spine motion during patient transfer onto a vacuum mattress with two stabilization techniques (head squeeze vs. trap squeeze) and two transfer methods (log roll with one assistant (LR2) vs. 3 assistants (LR4)). Methods. We used a crossover design to minimize bias. Each lead paramedic performed 10 LR2 transfers and 10 LR4 transfers. For each of the 10 LR2 and 10 LR4 transfers, the lead paramedic stabilized the cervical spine using the head squeeze technique five times and the trap squeeze technique five times. We randomized the order of the stabilization techniques and LR2/LR4 across lead paramedics to avoid a practice or fatigue effect with repeated trials. We measured relative cervical spine motion between the head and trunk using inertial measurement units placed on the forehead and sternum. Results. On average, total motion was 3.9° less with three assistants compared to one assistant (p = 0.0002), and 2.8° less with the trap squeeze compared to the head squeeze (p = 0.002). There was no interaction between the transfer method and stabilization technique. When examining specific motions in the six directions, the trap squeeze generally produced less lateral flexion and rotation motion but allowed more extension. Examining within paramedic differences, some paramedics were clearly more proficient with the trap squeeze technique and others were clearly more proficient with the head squeeze technique. Conclusion. Paramedics performing a log roll with three assistants created less motion compared to a log roll with only one assistant, and using the trap squeeze stabilization technique resulted in less motion than the head squeeze technique but the clinical relevance of the magnitude remains unclear. However, large individual differences suggest future paramedic training should incorporate both best evidence practice as well as recognition that there may be individual differences between paramedics.

Posturography Approaches: An Insightful Window to Explore the Role of the Brain in Socio-Affective Processes.

A significant amount of research has highlighted the importance of a motor component in the brain's processing of emotional, motivational and social information. Posturography has emerged as an interesting way to assess motor correlates associated with this process. In this review, we highlight recent results within the functional context of painful stimulus perception and discuss the interest in broadening the use of posturography to other motivational and societal functional contexts. Although characterized by significant feasibility, the single measurement of the COP's anteroposterior displacement presents limitations for attesting approach-avoidance behavior towards a visual target. Here, we discuss a number of methodological avenues that could go some way towards overcoming these limitations.

Estimated diameter increase from a 4S to a 6S hamstring graft configuration - A cadaveric study.

PURPOSE: Graft diameter in anterior cruciate ligament reconstructions has been shown to influence the risk of failure. It is therefore important to be able to adjust the graft configuration to modify the diameter. To measure the impact of a 6-strand (6S) hamstring autograft configuration on graft diameter compared to the standard 4-strand (4S) configuration. METHODS: Cadaveric study on 33 knees, using the usual hamstring graft harvesting technique. Semitendinosus and gracilis tendons were harvested and their length, width, and diameter were measured in 4S and 6S configurations separately by three evaluators. RESULTS: 6S configuration leads to a median increase of 1.5 (range: 0.0-2.0) mm in diameter compared to 4S (p < 0.001). A graft diameter of more than 8 mm is attained in less than a third of 4S grafts within this population in comparison to 84% when the 6S configuration is used. DISCUSSION: The 6S hamstring graft configuration increases the graft diameter by a median of 1.5 millimeters compared to the traditional 4S configuration. It can reliably be used to obtain an 8.5 mm graft diameter or more in cases where the semitendinosus measures at least 270.5 mm and the 4S configuration has a diameter of 7.5 mm or 8 mm. This information helps to better delineate the impact of a 6S configuration in a pre-operative or intra-operative setting to optimize the decisional process and surgical flow and to easily adapt the graft diameter. LEVEL OF EVIDENCE: V (cadaveric study).

Anterior Cruciate Ligament Sizing Tools Can Be Interchanged Without Affecting Graft Diameter Measurement.

Purpose: To determine whether different types of measurement tools can be interchanged without significantly affecting the resulting graft diameter. Methods: Hamstrings (gracilis and semitendinosus) and quadriceps tendons in 33 cadaver knees were harvested. Three different anterior cruciate ligament (ACL) graft combinations were created using these tendons, making 99 cadaver grafts samples available to measure. The grafts were randomly passed through sizing tubes and a slotted measurement block to determine their diameter. Interobserver and intraobserver reliabilities of measurements were assessed. Pearson correlation test, as well as Bland Altman graph, were used to evaluate the interchangeability of the tools. Results: In 95% of cases, the diameter difference between the tubes and the block measures was less than the 0.5 mm in increment cutoff. Both the intraobserver and interobserver reliability were excellent. Conclusions: This study showed that the ACL graft diameter measurement does not vary whether a slotted block or sizing tube from the same company is used. Clinical Relevance: ACL graft size has an influence on the surgical technique and clinical outcomes. Therefore it is important to have reliable sizing tools.

Removal of the cervical collar from alpine rescue protocols? A biomechanical non-inferiority trial in real-life mountain conditions.

BACKGROUND: Alpine skiing rescues are challenging because of the mountainous environment and risks of cervical spine motion (CSM) induced during victims' extrications (EXs) and downhill evacuations (DEs). The benefits of applying a cervical collar (CC) over manual in-line stabilization without CC (MILS) in terms of spinal motion restriction during simulated alpine rescues are undocumented. Our hypothesis was that CSM recorded using MILS alone is non-inferior to CSM recorded with a CC according to a 10 degrees margin. METHODS: A total of 32 alpine extrications and 4 downhill evacuations on different slope conditions were performed using a high fidelity mannequin designed with a motion sensors instrumented cervical spine. The primary outcome was the peak extrication 3D excursion angle (Peak 3D θEX,) of the mannequin's head. The secondary objectives were to describe the time to extrication completion (tEX) and to highlight which extrication manipulation is more likely to induce CSM. RESULTS: The median Peak 3D θEX recorded during flat terrain extrications using CC was 10.77° (95% CI 7.31°-16.45°) compared to 13.06° (95% CI 10.20°-30.36°) using MILS, and 16.09° (95% CI 9.07°-37.43°) for CC versus 16.65° (95% CI 13.80°-23.40°) using MILS on a steep slope. Peak 3D θEX with CC or using MILS during extrications were equivalent according to a 10 degrees non-inferiority hypothesis testing (p < 0.05). Time to extrication completion (tEX) was significantly reduced using MILS without CC on a flat terrain with a median duration of 237,3 s (95% CI 197.8 s, 272.2 s) compared to 358.7 s (95% CI 324.1 s, 472.4 s). During downhill evacuations, CSM with and without CC across all terrain conditions were negligible (< 5°). When CC is used; its installation manipulation induces the highest CSM. When EXs are done using MILS without CC, the logroll initiation is the manipulation inducing the highest risk of CSM. CONCLUSION: For experienced ski patrollers, the biomechanical benefits of spinal motion restriction provided by CC over MILS during alpine skiing rescues appear to be marginal and CC use negatively affects rescue time.

A Partial-Thickness Quadriceps Autograft Reliably Augments the Size of the Hamstring Graft During Anterior Cruciate Ligament Reconstruction.

Purpose: To measure the increase in diameter resulting from the augmentation of a hamstring autograft with a partial width rectus femoris tendon band in anterior cruciate ligament reconstruction. Methods: Thirty-three cadaveric knees were dissected to harvest semitendinosus and gracilis tendons (4S) along with a 6-mm wide tendon band from the rectus femoris. Harvesting was done according to the usual surgical techniques of both harvests. Measures of length and diameter in 4S and 4S augmented with the rectus femoris band (4S +Q) configurations were performed separately by 3 evaluators. Results: The quadriceps augmentation led to an average increase of 1.49 mm (95% confidence interval 1.03-1.95 mm) in diameter of the 4-strand hamstring grafts. The previously demonstrated threshold diameter of 8.5 mm was attained in only 30% of 4S grafts within this population in comparison with 88% when augmented with a quadriceps band. Conclusions: In conclusion, supplementing doubled hamstring graft (4S) with quadricipital tendon in anterior cruciate ligament reconstruction (ACLR) increases the graft diameter by an average of 1.49 mm. It has the physical potential to reliably augment hamstring grafts that measure 7.5 mm in diameter or more in order to obtain an 8.5 mm when necessitated. Clinical Relevance: Increased graft diameter is associated with a decreased risk of graft failure after ACLR. Because of this, it is important to identify methods to increase the size of grafts. This study investigates the use of a partial-width rectus femoris tendon band as an option to reliably augment graft sizes during ACLR.

Using ultrasound imaging to assess novice physiotherapy students' ability to locate musculoskeletal structures with palpation.

OBJECTIVE: Use ultrasound imaging to assess success rates of novice physiotherapy students attempting to locate two tendons and two joint spaces using palpation. DESIGN: Cross-sectional study. SETTING: Master of physiotherapy program at an academic institution. PARTICIPANTS: Twenty-two end of first-year physiotherapy students. METHODS: Participants were asked to palpate and locate the long head of the biceps (LHBT) and tibialis posterior (PTT) tendons as well as the acromioclavicular joint (ACJ) and medial tibiofemoral joint (TFJ) spaces on two human models. A truncated needle was taped onto the skin, parallel to the palpated structure. Ultrasound imaging was used to assess the position of the needle relative to the structures. MAIN OUTCOME MEASURES: Success or failure was determined based on a judgment call on the needle position relative to the targeted structure on the ultrasound images. Inter-evaluator agreement for judgment criteria was investigated using Cohen's kappa tests and success rates subsequently calculated. RESULTS: Kappa coefficients were 1.00 for all structures collectively, 1.00 for LHBT and PTT tendons, 1.006 for ACJ, and 0.79 for TFJ. Palpation success rates were: 9% for LHBT, 64% for PTT, 23% for ACJ, and 31% for medial TFJ. CONCLUSION: These results highlight the fact that there is room for improvement in anatomy and palpation skill teaching methods and ultrasound imaging is valuable tool to assess this important skill.

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.

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.

Quantitative Approach Based on Wearable Inertial Sensors to Assess and Identify Motion and Errors in Techniques Used during Training of Transfers of Simulated c-Spine-Injured Patients.

Patients with suspected spinal cord injuries undergo numerous transfers throughout treatment and care. Effective c-spine stabilization is crucial to minimize the impacts of the suspected injury. Healthcare professionals are trained to perform those transfers using simulation; however, the feedback on the manoeuvre is subjective. This paper proposes a quantitative approach to measure the efficacy of the c-spine stabilization and provide objective feedback during training. Methods. 3D wearable motion sensors are positioned on a simulated patient to capture the motion of the head and trunk during a training scenario. Spatial and temporal indicators associated with the motion can then be derived from the signals. The approach was developed and tested on data obtained from 21 paramedics performing the log-roll, a transfer technique commonly performed during prehospital and hospital care. Results. In this scenario, 55% of the c-spine motion could be explained by the difficulty of rescuers to maintain head and trunk alignment during the rotation part of the log-roll and their difficulty to initiate specific phases of the motion synchronously. Conclusion. The proposed quantitative approach has the potential to be used for personalized feedback during training sessions and could even be embedded into simulation mannequins to provide an innovative training solution.

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.