Improving activity recognition using a wearable barometric pressure sensor in mobility-impaired stroke patients.

© 2015 Massé et al.Background: Stroke survivors often suffer from mobility deficits. Current clinical evaluation methods, including questionnaires and motor function tests, cannot provide an objective measure of the patients mobility in daily life. Physical activity performance in daily-life can be assessed using unobtrusive monitoring, for example with a single sensor module fixed on the trunk. Existing approaches based on inertial sensors have limited performance, particularly in detecting transitions between different activities and postures, due to the inherent inter-patient variability of kinematic patterns. To overcome these limitations, one possibility is to use additional information from a barometric pressure (BP) sensor. Methods: Our study aims at integrating BP and inertial sensor data into an activity classifier in order to improve the activity (sitting, standing, walking, lying) recognition and the corresponding body elevation (during climbing stairs or when taking an elevator). Taking into account the trunk elevation changes during postural transitions (sit-to-stand, stand-to-sit), we devised an event-driven activity classifier based on fuzzy-logic. Data were acquired from 12 stroke patients with impaired mobility, using a trunk-worn inertial and BP sensor. Events, including walking and lying periods and potential postural transitions, were first extracted. These events were then fed into a double-stage hierarchical Fuzzy Inference System (H-FIS). The first stage processed the events to infer activities and the second stage improved activity recognition by applying behavioral constraints. Finally, the body elevation was estimated using a pattern-enhancing algorithm applied on BP. The patients were videotaped for reference. The performance of the algorithm was estimated using the Correct Classification Rate (CCR) and F-score. The BP-based classification approach was benchmarked against a previously-published fuzzy-logic classifier (FIS-IMU) and a conventional epoch-based classifier (EPOCH). Results: The algorithm performance for posture/activity detection, in terms of CCR was 90.4 %, with 3.3 % and 5.6 % improvements against FIS-IMU and EPOCH, respectively. The proposed classifier essentially benefits from a better recognition of standing activity (70.3 % versus 61.5 % [FIS-IMU] and 42.5 % [EPOCH]) with 98.2 % CCR for body elevation estimation. Conclusion: The monitoring and recognition of daily activities in mobility-impaired stoke patients can be significantly improved using a trunk-fixed sensor that integrates BP, inertial sensors, and an event-based activity classifier

Foreign Direct Investment, Intra-Regional Trade and Production Sharing in East Asia

The aim of this paper is twofold. First, it examines the trend and nature of East Asian trade. The United Nations BEC classification is utilized to categorize total trade into trade in semi-finished goods, trade in components and parts, trade in capital goods as well as trade in final consumption goods. It shows that the increasing importance of East Asia as a trading region is due at least partially to the rising trade in components and parts. Next, it tries to find out if foreign direct investment plays a role in the import and export behavior of East Asian intra-regional trade. Using a gravity model, it evidences that in general FDI is important in explaining imports and exports of intra-East Asian trade. In particular, FDI is especially important in explaining trade in components and parts, followed by trade in capital goods. This helps confirm that FDI and trade associated with production fragmentation in East Asia are complementary.

Temporal feature estimation during walking using miniature accelerometers: an analysis of gait improvement after hip arthroplasty

A new method for the detection of gait cycle phases using only two miniature accelerometers together with a light, portable digital recorder is proposed. Each subject is asked to walk on a walkway at his/her own preferred speed. Gait analysis was performed using an original method of computing the values of temporal parameters from accelerometer signals. First, to validate the accelerometric method, measurements are taken on a group of healthy subjects. No significant differences are observed between the results thus obtained and those from pressure sensors attached under the foot. Then, measurements using only accelerometers are performed on a group of 12 patients with unilateral hip osteo-arthritis. The gait analysis is carried out just before hip arthroplasty and again, three, six and nine months afterwards. A mean decrease of 88% of asymmetry of stance time and especially a mean decrease of 250% of asymmetry of double support time are observed, nine months after the operation. These results confirm the validity of the proposed method for healthy subjects and its efficiency for functional evaluation of gait improvement after arthroplast

In-field assessment of change-of-direction ability with a single wearable sensor.

The Agility T-test is a standardized method to measure the change-of-direction (COD) ability of athletes in the field. It is traditionally scored based on the total completion time, which does not provide information on the different CODs. Augmenting the T-test with wearable sensors provides the opportunity to explore new metrics. Towards this, data of 23 professional soccer players were recorded with a trunk-worn GNSS-IMU (Global Navigation Satellite System-Inertial Measurement Unit) device. A method for detecting the four CODs based on the wavelet-denoised antero-posterior acceleration signal was developed and validated using video data (60 Hz). Following this, completion time was estimated using GNSS ground speed and validated with the photocell data. The proposed method yields an error (mean ± standard deviation) of 0 ± 66 ms for the COD detection, - 0.16 ± 0.22 s for completion time, and a relative error for each COD duration and each sequential movement durations of less than 3.5 ± 16% and 7 ± 7%, respectively. The presented algorithm can highlight the asymmetric performance between the phases and CODs in the right and left direction. By providing a more comprehensive analysis in the field, this work can enable coaches to develop more personalized training and rehabilitation programs

ANALYSIS OF STABLE FLIGHT IN SKI JUMPING BASED ON PARAMETERS MEASURED WITH A WEARABLE SYSTEM

Biomechanics analysis of the ski jump is highly required. Some parameters and their interrelations have been reported in previous research studies limited to few athletes. The generalization of these parameters to athletes of various levels and under training conditions should be assessed, since they have the potential to be used for daily evaluation. This study proposed a new 3D approach based on inertial sensors to evaluate relevant kinematic and aerodynamic parameters of stable flight phase. The proposed wearable system can easily be used for daily training. Aerodynamic forces and body segments 3D angles were extracted during the stable flight phase of 86 jumps. Then, their correlations with respect to distance as well as their interrelations were analyzed. Their combination expressed 55% of the total distance variance

Quantifying dimensions of physical behavior in chronic pain conditions.

BACKGROUND: Chronic pain, defined as persistent or recurrent pain lasting longer than 3 months, is a frequent condition affecting an important percent of population worldwide. Pain chronicity can be caused by many different factors and is a frequent component of many neurological disorders. An important aspect for clinical assessment and design of effective treatment and/or rehabilitation strategies is to better understand the impact of pain on domains of functioning in everyday life. The aim of this study was to identify the objectively quantifiable features of physical functioning in daily life and to evaluate their effectiveness to differentiate behavior among subjects with different pain conditions. METHOD: Body worn sensors were used to record movement data during five consecutive days in 92 subjects. Sensor data were processed to characterize the physical behavior in terms of type, intensity, duration and temporal pattern of activities, postures and movements performed by subjects in daily life. Metrics quantifying these features were subsequently used to devise composite scores using a factor analysis approach. The severity of clinical condition was assessed using a rating of usual pain intensity on a 10-cm visual analog scale. The relationship between pain intensity and the estimated metrics/composite scores was assessed using multiple regression and discriminant analysis. RESULTS: According to the factor analysis solution, two composite scores were identified, one integrating the metrics quantifying the amount and duration of activity periods, and the other the metrics quantifying complexity of temporal patterns, i.e., the diversity of body movements and activities, and the manner in which they are organized throughout time. All estimated metrics and composite scores were significantly different between groups of subjects with clinically different pain levels. Moreover, analysis revealed that pain intensity seemed to have a more significant impact on the overall physical behavior, as it was quantified by a global composite score, whereas the type of chronic pain appeared to influence mostly the complexity of the temporal pattern. CONCLUSION: The methodology described could be informative for the design of objective outcome measures in chronic pain management/rehabilitation programs

Alteration and recovery of arm usage in daily activities after rotator cuff surgery.

BACKGROUND: The objective measurement of dominant/nondominant arm use proportion in daily life may provide relevant information on healthy and pathologic arm behavior. This prospective case-control study explored the potential of such measurements as indicators of upper limb functional recovery after rotator cuff surgery. METHODS: Data on dominant/nondominant arm usage were acquired with body-worn sensors for 7 hours. The postsurgical arm usage of 21 patients was collected at 3, 6, and 12 months after rotator cuff surgery in the sitting, walking, and standing postures and compared with a reference established with 41 healthy subjects. The results were calculated for the dominant and nondominant surgical side subgroups at all stages. The correlations with clinical scores were calculated. RESULTS: Healthy right-handed and left-handed dominant arm usage was 60.2% (±6.3%) and 53.4% (±6.6%), respectively. Differences in use of the dominant side were significant between the right- and left-handed subgroups for sitting (P = .014) and standing (P = .009) but not for walking (P = .328). The patient group showed a significant underuse of 10.7% (±8.9%) at 3 months after surgery (P < .001). The patients recovered normal arm usage within 12 months, regardless of surgical side. The arm underuse measurement was weakly related to function and pain scores. CONCLUSION: This study provided new information on arm recovery after rotator cuff surgery using an innovative measurement method. It highlighted that objective arm underuse measurement is a valuable indicator of upper limb postsurgical outcome that captures a complementary feature to clinical scores

A new ambulatory system for comparative evaluation of the three-dimensional knee kinematics, applied to anterior cruciate ligament injuries

The aim of this study was to develop an ambulatory system for the three-dimensional (3D) knee kinematics evaluation, which can be used outside a laboratory during long-term monitoring. In order to show the efficacy of this ambulatory system, knee function was analysed using this system, after an anterior cruciate ligament (ACL) lesion, and after reconstructive surgery. The proposed system was composed of two 3D gyroscopes, fixed on the shank and on the thigh, and a portable data logger for signal recording. The measured parameters were the 3D mean range of motion (ROM) and the healthy knee was used as control. The precision of this system was first assessed using an ultrasound reference system. The repeatability was also estimated. A clinical study was then performed on five unilateral ACL-deficient men (range: 19-36years) prior to, and a year after the surgery. The patients were evaluated with the IKDC score and the kinematics measurements were carried out on a 30m walking trial. The precision in comparison with the reference system was 4.4°, 2.7° and 4.2° for flexion-extension, internal-external rotation, and abduction-adduction, respectively. The repeatability of the results for the three directions was 0.8°, 0.7° and 1.8°. The averaged ROM of the five patients' healthy knee were 70.1° [standard deviation (SD) 5.8°], 24.0° (SD 3.0°) and 12.0° (SD 6.3°) for flexion-extension, internal-external rotation and abduction-adduction before surgery, and 76.5° (SD 4.1°), 21.7° (SD 4.9°) and 10.2° (SD 4.6°) 1year following the reconstruction. The results for the pathologic knee were 64.5° (SD 6.9°), 20.6° (SD 4.0°) and 19.7° (8.2°) during the first evaluation, and 72.3° (SD 2.4°), 25.8° (SD 6.4°) and 12.4° (SD 2.3°) during the second one. The performance of the system enabled us to detect knee function modifications in the sagittal and transverse plane. Prior to the reconstruction, the ROM of the injured knee was lower in flexion-extension and internal-external rotation in comparison with the controlateral knee. One year after the surgery, four patients were classified normal (A) and one almost normal (B), according to the IKDC score, and changes in the kinematics of the five patients remained: lower flexion-extension ROM and higher internal-external rotation ROM in comparison with the controlateral knee. The 3D kinematics was changed after an ACL lesion and remained altered one year after the surger

Physical Behavior in Older Persons during Daily Life: Insights from Instrumented Shoes.

Activity level and gait parameters during daily life are important indicators for clinicians because they can provide critical insights into modifications of mobility and function over time. Wearable activity monitoring has been gaining momentum in daily life health assessment. Consequently, this study seeks to validate an algorithm for the classification of daily life activities and to provide a detailed gait analysis in older adults. A system consisting of an inertial sensor combined with a pressure sensing insole has been developed. Using an algorithm that we previously validated during a semi structured protocol, activities in 10 healthy elderly participants were recorded and compared to a wearable reference system over a 4 h recording period at home. Detailed gait parameters were calculated from inertial sensors. Dynamics of physical behavior were characterized using barcodes that express the measure of behavioral complexity. Activity classification based on the algorithm led to a 93% accuracy in classifying basic activities of daily life, i.e., sitting, standing, and walking. Gait analysis emphasizes the importance of metrics such as foot clearance in daily life assessment. Results also underline that measures of physical behavior and gait performance are complementary, especially since gait parameters were not correlated to complexity. Participants gave positive feedback regarding the use of the instrumented shoes. These results extend previous observations in showing the concurrent validity of the instrumented shoes compared to a body-worn reference system for daily-life physical behavior monitoring in older adults