Wireless Motion Sensors Research Articles

Examination time-distance characteristics of gait and pelvic kinematics in individuals with Diabetic polyneuropathy: a case-control study

ABSTRACT Background Diabetic Peripheral Neuropathy (DPN) disrupts body and movement biomechanics, increases mechanical stress during walking, and predisposes individuals to injuries owing to the repetitive effects of these stresses. Aims This study aimed to assess and compare the impact of neuropathy on gait and pelvic kinematics in individuals with DPN. Methods This case-control study included two groups: 23 individuals diagnosed with DPN aged between 35–70 and 23 healthy individuals aged–35–70. The BTS-G, a wireless motion sensor, was used to assess the time-distance characteristics of walking in all participants. The system analyzed data pertaining to walking speed, cadence, percentages of stance and swing phases, durations of walking cycles, double-step lengths, pelvic tilt, obliquity, and rotation symmetries. Results There were no statistically significant differences between the groups in cadence, left and right stance phase percentages, or left and right swing phase percentages (p > 0.05). However, significant differences were observed between the groups in terms of speed, left and right walking cycle durations, and left and right double-step lengths (p < 0.05). Additionally, no statistically significant difference was found between the groups in pelvic tilt symmetry and left and right pelvic tilt range of motion values (p > 0.05). Nevertheless, significant differences were identified between the groups in pelvic obliquity symmetry, pelvic rotation symmetry, left and right pelvic obliquity range of motion, and left and right pelvic rotation range of motion values (p < 0.05). Conclusions The findings of this study suggest that individuals with DPN exhibit decreased walking speed, prolonged gait cycle duration, increased double step length, and reduced pelvic obliquity and rotation range of motion.

Can We Target Close Therapeutic Goals in the Gait Re-Education Algorithm for Stroke Patients at the Beginning of the Rehabilitation Process?

(1) Background: The study aimed to determine the most important activities of the knee joints related to gait re-education in patients in the subacute period after a stroke. We focused on the tests that a physiotherapist could perform in daily clinical practice. (2) Methods: Twenty-nine stroke patients (SG) and 29 healthy volunteers (CG) were included in the study. The patients underwent the 5-meter walk test (5mWT) and the Timed Up and Go test (TUG). Tests such as step up, step down, squat, step forward, and joint position sense test (JPS) were also performed, and the subjects were assessed using wireless motion sensors. (3) Results: We observed significant differences in the time needed to complete the 5mWT and TUG tests between groups. The results obtained in the JPS show a significant difference between the paretic and the non-paretic limbs compared to the CG group. A significantly smaller range of knee joint flexion (ROM) was observed in the paretic limb compared to the non-paretic and control limbs in the step down test and between the paretic and non-paretic limbs in the step forward test. (4) Conclusions: The described functional tests are useful in assessing a stroke patient's motor skills and can be performed in daily clinical practice.

A Wireless Motion Sensor Operating Down to −28-dBm Energy Harvesting

A Wireless Motion Sensor Operating Down to −28-dBm Energy Harvesting

Design of Wireless Motion Sensor Nodes based on the Kalman Filter Algorithm

Background: In recent years, wireless sensor network technology has been the center of attention in the international community. It has been a key element in e-health to monitor bodies. This technology enables new applications in different domains, including medical, physical training, etc. Method: Some sensors in WSN (Wireless Sensor Nodes) capture physiological data such as temperature, heartbeat and moving distance. The ECG signal is obtained by an analog front-end chip ADS1292 and processed by an adaptive Kalman filter algorithm. The sensor LMT70 is used to gather the body temperature; the acceleration sensor MPU6050 is used to detect, capture, recognize and identify other body gestures and motions data and the STM32F103C8 microprocessor is used as the kernel control module. WSN sensor nodes provide wireless monitoring due to transceiver module NRF24L01for anybody, anywhere and anytime. Result: Each measurement result can meet physiological index demands. Conclusion: The system can be used to avoid sports accidents and injuries and to plan for future training and realized in LAB conveniently owing to the high cost-performance ratio.

Feasibility of at-home motor assessments using wireless technology in patients with myelopathy: year 1 follow up of CYGNET, an observational study of patients with adrenomyeloneuropathy (P6-6.006)

Feasibility of at-home motor assessments using wireless technology in patients with myelopathy: year 1 follow up of CYGNET, an observational study of patients with adrenomyeloneuropathy (P6-6.006)

Concurrent validity of DorsaVi wireless motion sensor system Version 6 and the Vicon motion analysis system during lifting

BackgroundWearable sensor technology may allow accurate monitoring of spine movement outside a clinical setting. The concurrent validity of wearable sensors during multiplane tasks, such as lifting, is unknown. This study assessed DorsaVi Version 6 sensors for their concurrent validity with the Vicon motion analysis system for measuring lumbar flexion during lifting.MethodsTwelve participants (nine with, and three without back pain) wore sensors on T12 and S2 spinal levels with Vicon surface markers attached to those sensors. Participants performed 5 symmetrical (lifting from front) and 20 asymmetrical lifts (alternate lifting from left and right). The global-T12-angle, global-S2-angle and the angle between these two sensors (relative-lumbar-angle) were output in the sagittal plane. Agreement between systems was determined through-range and at peak flexion, using multilevel mixed-effects regression models to calculate root mean square errors and standard deviation. Mean differences and limits of agreement for peak flexion were calculated using the Bland Altman method.ResultsFor through-range measures of symmetrical lifts, root mean squared errors (standard deviation) were 0.86° (0.78) at global-T12-angle, 0.90° (0.84) at global-S2-angle and 1.34° (1.25) at relative-lumbar-angle. For through-range measures of asymmetrical lifts, root mean squared errors (standard deviation) were 1.84° (1.58) at global-T12-angle, 1.90° (1.65) at global-S2-angle and 1.70° (1.54) at relative-lumbar-angle. The mean difference (95% limit of agreement) for peak flexion of symmetrical lifts, was − 0.90° (-6.80 to 5.00) for global-T12-angle, 0.60° (-2.16 to 3.36) for global-S2-angle and − 1.20° (-8.06 to 5.67) for relative-lumbar-angle. The mean difference (95% limit of agreement) for peak flexion of asymmetrical lifts was − 1.59° (-8.66 to 5.48) for global-T12-angle, -0.60° (-7.00 to 5.79) for global-S2-angle and − 0.84° (-8.55 to 6.88) for relative-lumbar-angle.ConclusionThe root means squared errors were slightly better for symmetrical lifts than they were for asymmetrical lifts. Mean differences and 95% limits of agreement showed variability across lift types. However, the root mean squared errors for all lifts were better than previous research and below clinically acceptable thresholds. This research supports the use of lumbar flexion measurements from these inertial measurement units in populations with low back pain, where multi-plane lifting movements are assessed.

Fusion classification of stroke patients' biosignals by weighted cross-validation-based feature selection (W-CVFS) method

A multi-source information fusion-based disease class classification of stroke patients was implemented to address the low classification accuracy of pure input motion and electromyographic signals. sEMG sensor MYO arm ring and wearable wireless motion sensor Shimmer were used as data acquisition devices. The Butterworth high-pass filter filtering and envelope thresholding method detected the activity segment. Detection and FIR filtering using the window function method remove interference from the motion signal. A weighted cross-validation-based feature selection (W-CVFS) method is proposed for feature fusion selection. The top 10 features selected by the W-CVFS method and all 18 features are input to the deep neural network for training and testing, and the feature classification result of the W-CVFS method is 79.17%, which is better than the existing mRMR method (66.67%) and ILFS method (62.50%). The classificatip9uon accuracy of multi-source information fusion was 95.385%, which was higher than that of a single input motion signal or sEMG. The experiments showed that the proposed method can retain the features that have more influence on the classification results and can improve the classification accuracy of the rehabilitation model for stroke patients.

A self-powered wireless motion sensor based on a high-surface area reverse electrowetting-on-dielectric energy harvester

This paper presents a motion-sensing device with the capability of harvesting energy from low-frequency motion activities. Based on the high surface area reverse electrowetting-on-dielectric (REWOD) energy harvesting technique, mechanical modulation of the liquid generates an AC signal, which is modeled analytically and implemented in Matlab and COMSOL. A constant DC voltage is produced by using a rectifier and a DC–DC converter to power up the motion-sensing read-out circuit. A charge amplifier converts the generated charge into a proportional output voltage, which is transmitted wirelessly to a remote receiver. The harvested DC voltage after the rectifier and DC–DC converter is found to be 3.3 V, having a measured power conversion efficiency (PCE) of the rectifier as high as 40.26% at 5 Hz frequency. The energy harvester demonstrates a linear relationship between the frequency of motion and the generated output power, making it highly suitable as a self-powered wearable motion sensor.

Low-Complexity Design and Validation of Wireless Motion Sensor Node to Support Physiotherapy.

We present a motion sensor node to support physiotherapy, based on an Inertial Measurement Unit (IMU). The node has wireless interfaces for both data exchange and charging, and is built based on commodity components. It hence provides an affordable solution with a low threshold to technology adoption. We share the hardware design and explain the calibration and validation procedures. The sensor node has an autonomy of 28 h in operation and a standby time of 8 months. On-device sensor fusion yields static results of on average ° with a drift of 2° per half hour. The final prototype weighs 38 g and measures ø6 cm × cm. The resulting motion sensor node presents an easy to use device for both live monitoring of movements as well as interpreting the data afterward. It opens opportunities to support and follow up treatment in medical cabinets as well as remotely.

Wearable Smart Health Advisors: An IMU-Enabled Posture Monitor

Unhealthy life habits are associated with a large number of chronic conditions in our modern lifestyle. Many commercialized wearable solutions have already been developed for monitoring and prevention purposes, while recent design efforts aim for more user-friendly and reliable solutions. In this context, due to the increased periods of sitting at work or home, improper sitting posture is related to numerous health disorders of the musculoskeletal system. Therefore, continuous stance monitoring can be used to improve users' sitting habits. In this article, we present an overview of wearable self-care devices and describe a monitoring system for a sitting posture that utilizes wireless motion sensors attached to the user's back. The developed prototype relies on inertial measurement units able to track the angle deviation from the optimal position which is learned during a training phase. Additionally, in order to support stance visualization and track the user's performance over time, our framework utilizes a cloud-native mobile application. The proposed system is experimentally evaluated resulting in an accurate everyday solution that prevents chronic improper posture.

Hofmeister-Effect-Guided Ionohydrogel Design as Printable Bioelectronic Devices.

Bioelectronic platforms convert biological signals into electrical signals by utilizing biocatalysts that provide tools to monitor the activity of cells and tissues. Traditional conducting materials such as solid conductors and conducting polymers are confronted with a great challenge in sophisticated production processes and mismatch at biological tissues-machine interfaces. Furthermore, the biocatalyst, the key functional component in the electron-transfer reaction for bio-signal detection denatures easily in an ionic conductive solution. Herein, a bionic strategy is elaborately developed to synthesize an ionohydrogel bioelectronic platform that possesses extracellular-matrix-like habitat by employing hydrated ionic liquids (HILs) as ionic solvent and bioprotectant. This strategy realizes an integration of ionic and enzymatic electronic circuits and minimization of the disparities between tissues and artificial machines. The Hofmeister effect of HILs on enzyme proteins and polymer chains ensures the high bioactivity of the enzymes and greatly improves the mechanical properties of the ionohydrogels. Moreover, hydrogen bonds formed by ILs, water, and polymer chains greatly improve the water-retention of the ionohydrogel and give it more practical significance. Consequently, the promising ionohydrogel is partly printed and fabricated into wearable devices as a pain-free humoral components monitor and a wireless motion-sensor.

Wireless Motion Sensors-Useful in Assessing the Effectiveness of Physiotherapeutic Methods Used in Patients with Knee Osteoarthritis-Preliminary Report.

Osteoarthritis of the knee (OAK) is characterized by pain, limitation of joint mobility, and significant deterioration of proprioception resulting in functional decline. This study assessed proprioception in OAK patients following two ten-day rehabilitation programs using the Orthyo® system. Fifty-four study participants with clinical symptoms and radiological signs of OAK were randomly divided into an exercise group (n = 27) or a manual therapy group (n = 27). The control group consisted of 27 volunteers with radiological signs of OAK, but with no clinical symptoms or prior history of rehabilitation. The following parameters were assessed: knee proprioception using inertial sensors and a mobile application, patients’ function using Western Ontario and McMaster Universities osteoarthritis index (WOMAC), and pain intensity using the visual analog scale (VAS). Following rehabilitation, knee proprioception tests did not improve in either study group. Both study groups showed significant improvement of the WOMAC-assessed function (exercise group: p < 0.01, manual therapy group: p = 0.01) and a significant decrease (p < 0.01) of VAS-assessed pain following rehabilitation, but the post-therapy results did not differ significantly between the aforementioned groups. The Orthyo® system provided a quick and accurate assessment of the knee joint position sense. There was no direct relationship between functionality, pain, and proprioception threshold in the knee joint.

A Motion-Detection Electronic Hand Hygiene Verbal Reminder Increases Adherence in a Standard Precaution Room

BACKGROUND Hand hygiene rates remain suboptimal. We previously reported the effect of a motion-detection verbal hand hygiene reminder installed at the door of a contact isolation room and on hand hygiene for nurses, versus all others. This study evaluates the device's effect on the hand hygiene rate for a standard precaution hospital room. METHODS A wireless motion sensor was installed above a standard precaution room door. When an individual entered or exited the room, the device's speaker announced a verbal hand hygiene reminder. The individual was credited with adherence by secret observers only if observed to wash hands at both entry and exit. This prospective study included 174 baseline measurements (before motion-detection sensor deployed) and 111 measurements during the intervention period (the period during which the sensor was installed), for a total of 285 observations. RESULTS Before the wireless sensor was deployed, we found that without the verbal reminder, 6% (n=11) washed their hands at both entry and exit and 94% (n=163) did not. During the intervention, adherence increased to 38% (n=42), while 62% (n=69) did not. As different individuals might be observed before and after sensor installation, we performed a chi-square test for independence using Yates’ correction for continuity with SPSS 25 to compare rates of adherence. With the sensor, there was a statistically significant (X(squared)Yates(1) = 42.41, φ = .40, p CONCLUSIONS In this study, the use of a wireless motion sensor to provide verbal reminders significantly increased hand hygiene adherence at both entry and exit for a standard precaution room. Thus, an audio reminder triggered by motion detection can increase hand hygiene adherence and may curb the incidence of nosocomial infections.

Are Measures of Postural Behavior Using Motion Sensors in Seated Office Workers Reliable?

In this study, the reliability of measures of upper body postural behavior (head, thorax, neck, and arm) during sustained office work was evaluated. Although there has been a substantial body of research examining the technical aspects of posture measurement in office workers using motion sensors, there is a paucity of literature examining whether posture-related behaviors are actually consistent among office workers in the field on different days and times. Thirty one office workers performed their usual work for three, 1-hr sessions (two morning sessions and one afternoon session) while wearing wireless motion sensors. Reliability coefficients of the derived measures of postural behavior were calculated. Most (30/31) of the postural behavior measures demonstrated modest to excellent reliability (ICC 2.1: 0.48-0.84). Reliability appeared to be mildly affected by factors such as the time of day recordings were taken and variations in desk setups. The findings suggest these measures may be a reliable method for evaluating postural behavior in the office work environment in future studies. Postural measurement using a technical motion sensor described an acceptable reliability to be used for risk assessment in the workplace. Consideration of assessment time and desk setting would increase the accuracy of postural measurement.

Altered trunk head co-ordination in those with persistent neck pain

BackgroundDecreased neck motion and sensorimotor deficits have been identified in those with neck pain. It is thought that these might be related to altered reflex mechanisms between the neck, eyes and the vestibular system. Trunk, head co-ordination might also be altered in neck pain. ObjectivesThis study investigated trunk head co-ordination ability in subjects with neck pain compared to asymptomatic controls. MethodTwenty–four subjects with persistent neck pain and twenty-six age and gender matched healthy controls performed 3 trials of 3 trunk movements whilst trying to keep the head still - (1) alternate trunk movement to the left and right (2) trunk movement to the left (3) trunk movement to the right. Wireless motion sensors positioned over the sternum and the forehead measured trunk and head range and velocity of motion. AnalysisANOVA was used to compare trunk and head range and velocity of motion during the 3 tasks. ResultsNeck pain subjects had significantly less trunk movement (p < 0.05) and velocity (p=<0.02) as well as significantly increased head movement (p=<0.03) during most tasks compared to control subjects. DiscussionThe results of the study suggest that neck pain subjects have difficulty moving their trunk independently of their head. They are less able to keep the head still while moving the trunk and perform the tasks more slowly. These findings might be related to altered reflex activity of the cervico-collic reflex and sensorimotor control. Further research is required.

Can Virtual Reality, Interactive Game, and Body Motion Sensors be a Replacement for General Anesthesia in Children Receiving Radiation Therapy?

To keep some young patients still during the daily radiation treatment (XRT) requires general anesthesia, which is expensive, time demanding, and has short and long-term consequences to these young patients. This study investigate a noninvasive technique using virtual reality (VR), interactive game, and body motion sensors to keep young patients to remain still during XRT, in place of general anesthesia. The proposed VR system consists of: (1) Head Mounted Display (HMD) that can display 3-D 1080p video and audio; (2) Multiple wireless motion sensors attached to body, arms and legs; (3) multi-level 3-D games(4) the computer system that incorporates all these components and provide output to patients and technicians. The Bluetooth motion sensors have 6 degree of freedom and provide instantaneous motion signal (rotation and translation) and are integrated into the game play. The game component will feature patient as an avatar flying an aero-skateboard to help mother dinosaur to collect all the lost eggs through multiple terrains (game levels) of forest, desert, mountain, etc. Positive feedback given as scores and bonus throughout the process to stimulate the patient during the 30-45 minute duration of the treatment. Once the patient is set in the reference position (, i.e., simulation position) and the game starts, as long as the patient remains still, the avatar will fly and collect eggs with different colors and adding scores. If motion of any body parts is detected above certain set threshold, the avatar is stopped, and warning is given to patients and therapist computer console indicating which part of needed to be still or resume to reference position. Once this is done, the game resumes. The therapist can hear and see what patients see, and there are two-way communication between patients and therapist. At the end of the session, depending on the score, the patient will be rewarded with toys. A prototype has been developed and has been tested in 15 healthy young children from age 4 to 10. After a few attempts, all children can comprehend and remain still for at least 30 min. Some adjustments in the gameplay and additional game levels were made to keep patients engaged. The proposed VR system can potentially offer an alternative to general anesthesia in some children undergoing XRT. This can significantly reduce morbidity, cost, and inefficiency in the radiation treatment of pediatric population. The next step is to perform a pilot clinical study on actual pediatric patients undergoing radiation treatments.

Subgroups of lumbo-pelvic flexion kinematics are present in people with and without persistent low back pain

BackgroundMovement dysfunctions have been associated with persistent low back pain (LBP) but optimal treatment remains unclear. One possibility is that subgroups of persistent LBP patients have differing movement characteristics and therefore different responses to interventions. This study examined if there were patterns of flexion-related lumbo-pelvic kinematic and EMG parameters that might define subgroups of movement.MethodsThis was a cross-sectional, observational study of 126 people without any history of significant LBP and 140 people with persistent LBP (n = 266). Wireless motion and surface EMG sensors collected lumbo-pelvic data on flexion parameters (range of motion (ROM) of trunk, lumbar, and pelvis), speed, sequence coordination and timing, and EMG extensor muscle activity in forward bending (flexion relaxation)), and sitting parameters (relative position, pelvic tilt range and tilt ratio). Latent class analysis was used to identify patterns in these parameters.ResultsFour subgroups with high probabilities of membership were found (mean 94.9%, SD10.1%). Subgroup 1 (n = 133 people, 26% LBP) had the greatest range of trunk flexion, fastest movement, full flexion relaxation, and synchronous lumbar versus pelvic movement. Subgroup 2 (n = 73, 71% LBP) had the greatest lumbar ROM, less flexion relaxation, and a 0.9 s lag of pelvic movement. Subgroup 3 (n = 41, 83% LBP) had the smallest lumbar ROM, a 0.6 s delay of lumbar movement (compared to pelvic movement), and less flexion relaxation than subgroup 2. Subgroup 4 (n = 19 people, 100% LBP) had the least flexion relaxation, slowest movement, greatest delay of pelvic movement and the smallest pelvic ROM. These patterns could be described as standard (subgroup 1), lumbar dominant (subgroup 2), pelvic dominant (subgroup 3) and guarded (subgroup 4). Significant post-hoc differences were seen between subgroups for most lumbo-pelvic kinematic and EMG parameters. There was greater direction-specific pain and activity limitation scores for subgroup 4 compared to other groups, and a greater percentage of people with leg pain in subgroups 2 and 4.ConclusionFour subgroups of lumbo-pelvic flexion kinematics were revealed with an unequal distribution among people with and without a history of persistent LBP. Such subgroups may have implications for which patients are likely to respond to movement-based interventions.

Real-Time Human Physical Activity Recognition with Low Latency Prediction Feedback Using Raw IMU Data.

In the realm of Human Activity Recognition (HAR), supervised machine learning and deep learning are commonly used. Their training is done using time and frequency features extracted from raw data (inertial and gyroscopic). Nevertheless, raw data are seldom employed. In this paper, a dataset of able-bodied participants is recorded using 3 custom wireless motion sensors providing embedded IMU and sEMG detection and processing and a base station (a Raspberry Pi 3) running a classification algorithm. A Support Vector Machine with Radius Basis Function Kernel (RBF-SVM) is augmented using Spherical Normalization to achieve a motion classification accuracy of 97.35% between 8 body motions. The proposed classifier allows for real-time prediction callback with low latency output.

Effects of Head-Mounted Display on kinematics of the Timed Up and GO (TUG) test: does the addition of a visual stimulus matter?

Effects of Head-Mounted Display on kinematics of the Timed Up and GO (TUG) test: does the addition of a visual stimulus matter?

Effect of Hip Abduction Maximal Voluntary Isometric Contraction on Lumbar Motion and Power Output During the Back Squat

Background: Post-activation potentiation (PAP) is a neuromuscular phenomenon that has been shown to augment muscular force generating attributes as well as neural and sensory recruitment. While PAP has demonstrated to acutely enhance muscular performance during high-intensity activities, the effect of PAP on lumbopelvic kinematics under load remains unknown. Objectives: The purpose of this study was to examine the potential PAP effect of a hip abduction maximal voluntary isometric contraction (MVIC) on lumbar motion and power output during the barbell back squat. Methods: Nine resistance-trained men (22.9±2.3 y; 85.0±13.8 kg; 174.3±5.1 cm) performed a set of 5 repetitions of the barbell back squat using 80% one-repetition maximum with and without a hip abduction MVIC prior to performance. Experimental and control trials were randomized and counterbalanced among participants. MVIC was carried out via manual long-lever hip abduction. During the back squat exercise, lumbar motion analysis was performed using wireless motion-sensor technology, and power output was assessed via an accelerometer. Results: No significant differences were observed between trials for lumbar flexion range of motion (ROM) (p=0.32), lumbar flexion maximum deviation (p=0.32), lumbar lateral flexion ROM (p=0.81), lumbar lateral flexion maximum deviation (p=0.98), lumbar rotation maximum deviation (p=0.70), average peak power (p=0.98), or average mean power output (p=0.99) during the squat protocol. Conclusions: Implementation of a manual long-lever hip abduction MVIC prior to the back squat exercise did not significantly alter lumbar motion or augment power output in resistance trained males.