Effects of infant care posture and weight on static postural balance.

BACKGROUND: Studies investigating postural balance during various infant care postures have not been reported yet. OBJECTIVE: The aim of this study was to measure static postural balance when holding an infant dummy in-arms and carrying an infant dummy on back according to different infant dummy weights. METHODS: Sixteen healthy young subjects participated in a balance test. Infant dummies with weights of 4.6 kg (1-month) and 9.8 kg (12-month) were used in this study. All subjects were asked to naturally stand on a force platform in two infant care postures (holding an infant in-arms and carrying an infant on one's back). Center of pressure (COP) was measured from the force platform. Quantitative variables were derived from the COP. Two-way repeated measure analysis of variance (ANOVA) was performed to determine main effects of infant care postures, infant weight, and their interactions on COP variables. RESULTS: Back carrying a 12-month infant dummy had the greatest amplitude in all COP variables. Back carrying posture showed significantly greater mean distance and peak power, faster mean velocity, and wider COP area compared to holding posture (P< 0.05). There were significant weight effects of most COP variables mainly in AP direction (P< 0.01). CONCLUSIONS: Our results could contribute to the prevention of musculoskeletal diseases or prevention of fall due to various infant care activities by developing an assisting device to improve postural balance.

Ground Force Precision Calibration Method for Customized Piezoresistance Sensing Flexible Force Measurement Mat.

A force plate is mainly used in biomechanics; it aims to measure the ground reaction force in a person's walking or standing position. In this study, a large-area force mat of the piezoresistance sensing type was developed, and a deep-learning-based weight measurement calibration method was applied to solve the problem in which measurements are not normalized because of physical limitations in hardware and signal processing. The test set was composed of the values measured at each point by weight and the value of the center of the pressure variable, and the measured value was predicted using a deep neural network (DNN) regression model. The calibration verification results show that the average weight errors range from a minimum of 0.06% to a maximum of 3.334%. This is simpler than the previous method, which directly measures the ratio of the resistance value to the measured weight of each sensor and derives an equation.

Adaptive Control Method for Gait Detection and Classification Devices with Inertial Measurement Unit.

Cueing and feedback training can be effective in maintaining or improving gait in individuals with Parkinson's disease. We previously designed a rehabilitation assist device that can detect and classify a user's gait at only the swing phase of the gait cycle, for the ease of data processing. In this study, we analyzed the impact of various factors in a gait detection algorithm on the gait detection and classification rate (GDCR). We collected acceleration and angular velocity data from 25 participants (1 male and 24 females with an average age of 62 ± 6 years) using our device and analyzed the data using statistical methods. Based on these results, we developed an adaptive GDCR control algorithm using several equations and functions. We tested the algorithm under various virtual exercise scenarios using two control methods, based on acceleration and angular velocity, and found that the acceleration threshold was more effective in controlling the GDCR (average Spearman correlation -0.9996, p < 0.001) than the gyroscopic threshold. Our adaptive control algorithm was more effective in maintaining the target GDCR than the other algorithms (p < 0.001) with an average error of 0.10, while other tested methods showed average errors of 0.16 and 0.28. This algorithm has good scalability and can be adapted for future gait detection and classification applications.

Quantitative Analysis of Postural Balance in Faller and Nonfaller Patients with Parkinson's Disease.

Background: Postural instability has been identified as a fall risk factor with a significant impact on the quality of life of patients with Parkinson's disease (PD). The aim of this study was to compare the center of pressure (COP) between faller and nonfaller patients with PD during static standing. Methods: Thirty-two faller patients and 32 nonfaller patients with PD participated in this study. All patients performed the static balance test on a force plate. COP data were recorded during quiet standing. Mean distance, sway area, mean velocity, mean frequency, and peak power were derived from the COP data. Statistical analysis was performed using independent t-tests to compare faller and nonfaller patients. Results: Fallers presented a greater average distance, wider sway area, faster average speed, and greater peak power than nonfallers (p < 0.05). In contrast, no significant group differences were observed in peak frequency and mean frequency (p > 0.05). Conclusions: Although falls occur during dynamic activities, our study demonstrated that even a safe and simple static postural balance test could significantly differentiate between faller and nonfaller patients. Thus, these results suggest that quantitatively assessed static postural sway variables would be useful for distinguishing prospective fallers among PD patients.

Comparison of resting tremor at the upper limb joints between patients with Parkinson's disease and scans without evidence of dopaminergic deficit.

BACKGROUND: A representative symptom of Parkinson's disease (PD) is resting tremor. The clinical manifestation of scans without evidence of dopaminergic deficit (SWEDD) is similar to it of PD, though the phenomenology of SWEDD is not well known. OBJECTIVE: In the present study, the resting tremor of 9 SWEDD patients was quantitatively compared with that of 11 PD patients. METHODS: Four 3-axis gyro sensors were attached on the index finger, thumb, dorsum of the hand, and arm of the more tremulous side. Root mean square (RMS) angular speed and angular displacement as well as irregularity of angular speed and displacement were derived from the sensor data. RESULTS: Although disease duration and Hoehn and Yahr stages were comparable, SWEDD patients exhibited different tremor features from PD patients. Significantly faster RMS angular speed and greater RMS angular displacement (p< 0.05) were observed in PD patients than in SWEDD patients. The irregularity of angular displacement of pitch direction at the dorsum of the hand was greater in SWEDD patients than in PD patients (p< 0.05). CONCLUSION: These results indicate that quantitative indices obtained from resting tremor task could be important biomarkers for identifying potential patients with SWEDD among patients diagnosed with PD.

Time-efficient implantable catheters for draining malignant ascites in terminal cancer patients.

BACKGROUND: There is a need for an improved version of the implantable catheter for malignant ascites in the abdominal cavity. OBJECTIVE: New implantable catheters have been developed that drain ascites from the abdominal cavity to the bladder by applying pressure. Based on pigtail catheters, these newly designed catheters have silicone membranes and apertures. METHODS: Experimental instruments controlled flow rates and water level to observe changes of the activation pressure and its cycle time along flow rates and turns of catheters. Furthermore, various normality tests, difference tests and non-parametric tests were investigated to observe statistical validity. RESULTS: Cycle times were significantly affected by flow rate (3/4 cases of p< 0.05). The effects of flow rate on activation pressure, however, were not significant (1/4 case of p< 0.05). Cycle times were not significantly affected by the number of turns of the catheter (3/8 cases of p< 0.05). In contrast, the effects of the turns on activation pressure were significant (5/8 cases of p< 0.05). CONCLUSION: Overall, there was no significant difference between cycle times for 1.5 turns and 2.0 turns of catheters. In addition, catheters with 1.5 turns have a lower activation pressure than catheters with 2.0 turns. It is possible to customize catheters based on the ascites excretion and urination rates of various terminal patients.

Age-related differences in the quantitative analysis of the finger tapping task.

BACKGROUND: Quantitative measures of the finger tapping task is important for objective assessment of bradykinesia. However, age-related changes in quantitative measures are still unclear. OBJECTIVE: The aim of this study was to quantitatively investigate age-related group differences in finger tapping performance. METHODS: Eighty-three healthy normal subjects with age ranging from aged 20 to 89 years participated in this study. All subjects were instructed to tap their index finger and thumbs as rapidly as possible and with as large amplitude as possible. Angular velocity of the finger tapping movement was measured using a gyrosensor. Quantitative variables include root mean squared (RMS) angular velocity, RMS angular displacement, peak power and peak frequency derived from angular velocity signals. RESULTS: Significant age-related differences were observed in RMS angular velocity, peak power and peak frequency (P< 0.001). Specifically, the oldest age group had the slowest average speed, the lowest peak power and peak frequency. These results indicate deterioration in finger speed, intensity of the main movement component and tapping frequency due to aging. CONCLUSIONS: The results suggest that the quantitative variables should be adjusted for age when clinicians assess Parkinsonian bradykinesia. The results contribute to the development of an accurate and quantitative assessment tool for bradykinesia.

Gait Disorder Detection and Classification Method Using Inertia Measurement Unit for Augmented Feedback Training in Wearable Devices.

Parkinson's disease (PD) is a common neurodegenerative disease, one of the symptoms of which is a gait disorder, which decreases gait speed and cadence. Recently, augmented feedback training has been considered to achieve effective physical rehabilitation. Therefore, we have devised a numerical modeling process and algorithm for gait detection and classification (GDC) that actively utilizes augmented feedback training. The numerical model converted each joint angle into a magnitude of acceleration (MoA) and a Z-axis angular velocity (ZAV) parameter. Subsequently, we confirmed the validity of both the GDC numerical modeling and algorithm. As a result, a higher gait detection and classification rate (GDCR) could be observed at a higher gait speed and lower acceleration threshold (AT) and gyroscopic threshold (GT). However, the pattern of the GDCR was ambiguous if the patient was affected by a gait disorder compared to a normal user. To utilize the relationships between the GDCR, AT, GT, and gait speed, we controlled the GDCR by using AT and GT as inputs, which we found to be a reasonable methodology. Moreover, the GDC algorithm could distinguish between normal people and people who suffered from gait disorders. Consequently, the GDC method could be used for rehabilitation and gait evaluation.

Quantitative measures of postural tremor at the upper limb joints in patients with essential tremor.

BACKGROUND: It is important to quantitatively assess tremor for accurate diagnosis and evaluation of the response to interventions in patients with essential tremor (ET). OBJECTIVE: The purpose of this study was to investigate the relationship between quantitative measures of postural tremor and clinical rating scale in patients with ET. METHODS: 18 ET patients performed a postural tremor task that required them to hold their arms outstretched parallel to the floor while wearing a gyro sensor based measurement system. The time domain variables were derived from the sensor signals. Additionally, the frequency domain variables were derived from the power spectrum of the angular velocity signal. Spearman correlation analysis was employed in the relationship between the variables and clinical score. RESULTS: The RMS angular velocity of roll and yaw directions at the hand joint were strongly correlated with the clinical rating scale (r= 0.7, p< 0.01). Similarly, the peak power of roll and yaw directions at the hand joint were moderately correlated with the clinical rating scale (r= 0.61 and r= 0.67, p< 0.01). In contrast, no significant correlation coefficients were observed in the peak frequency (p> 0.05). CONCLUSION: These results indicate that hand tremor of roll and yaw directions are more associated with assessment of severity of ET compared to other joints. This study suggests that quantitative measurements of postural tremor should be considered as tremor directionality as well as attachment location.

Design and fabrication of auxetic PCL nanofiber membranes for biomedical applications.

The main objective of this study was to fabricate poly (ε-caprolactone) (PCL)-based auxetic nanofiber membranes and characterize them for their mechanical and physicochemical properties. As a first step, the PCL nanofibers were fabricated by electrospinning with two different thicknesses of 40µm (called PCL thin membrane) and 180µm (called PCL thick membrane). In the second step, they were tailored into auxetic patterns using femtosecond laser cut technique. The physicochemical and mechanical properties of the auxetic nanofiber membranes were studied and compared with the conventional electrospun PCL nanofibers (non-auxetic nanofiber membranes) as a control. The results showed that there were no significant changes observed among them in terms of their chemical functionality and thermal property. However, there was a notable difference observed in the mechanical properties. For instance, the thin auxetic nanofiber membrane showed the magnitude of elongation almost ten times higher than the control, which clearly demonstrates the high flexibility of auxetic nanofiber membranes. This is because that the auxetic nanofiber membranes have lesser rigidity than the control nanofibers under the same load which could be due to the rotational motion of the auxetic structures. The major finding of this study is that the auxetic PCL nanofiber membranes are highly flexible (10-fold higher elongation capacity than the conventional PCL nanofibers) and have tunable mechanical properties. Therefore, the auxetic PCL nanofiber membranes may serve as a potent material in various biomedical applications, in particular, tissue engineering where scaffolds with mechanical cues play a major role.

Biomaterial Strategies for Delivering Stem Cells as a Treatment for Spinal Cord Injury.

Ongoing clinical trials are evaluating the use of stem cells as a way to treat traumatic spinal cord injury (SCI). However, the inhibitory environment present in the injured spinal cord makes it challenging to achieve the survival of these cells along with desired differentiation into the appropriate phenotypes necessary to regain function. Transplanting stem cells along with an instructive biomaterial scaffold can increase cell survival and improve differentiation efficiency. This study reviews the literature discussing different types of instructive biomaterial scaffolds developed for transplanting stem cells into the injured spinal cord. We have chosen to focus specifically on biomaterial scaffolds that direct the differentiation of neural stem cells and pluripotent stem cells since they offer the most promise for producing the cell phenotypes that could restore function after SCI. In terms of biomaterial scaffolds, this article reviews the literature associated with using hydrogels made from natural biomaterials and electrospun scaffolds for differentiating stem cells into neural phenotypes. It then presents new data showing how these different types of scaffolds can be combined for neural tissue engineering applications and provides directions for future studies.

Electrospun biomaterial scaffolds with varied topographies for neuronal differentiation of human-induced pluripotent stem cells.

In this study, we investigated the effect of micro and nanoscale scaffold topography on promoting neuronal differentiation of human induced pluripotent stem cells (iPSCs) and directing the resulting neuronal outgrowth in an organized manner. We used melt electrospinning to fabricate poly (ε-caprolactone) (PCL) scaffolds with loop mesh and biaxial aligned microscale topographies. Biaxial aligned microscale scaffolds were further functionalized with retinoic acid releasing PCL nanofibers using solution electrospinning. These scaffolds were then seeded with neural progenitors derived from human iPSCs. We found that smaller diameter loop mesh scaffolds (43.7 ± 3.9 µm) induced higher expression of the neural markers Nestin and Pax6 compared to thicker diameter loop mesh scaffolds (85 ± 4 µm). The loop mesh and biaxial aligned scaffolds guided the neurite outgrowth of human iPSCs along the topographical features with the maximum neurite length of these cells being longer on the biaxial aligned scaffolds. Finally, our novel bimodal scaffolds also supported the neuronal differentiation of human iPSCs as they presented both physical and chemical cues to these cells, encouraging their differentiation. These results give insight into how physical and chemical cues can be used to engineer neural tissue.

Fabrication of poly (ϵ-caprolactone) microfiber scaffolds with varying topography and mechanical properties for stem cell-based tissue engineering applications.

Highly porous poly (ϵ-caprolactone) microfiber scaffolds can be fabricated using electrospinning for tissue engineering applications. Melt electrospinning produces such scaffolds by direct deposition of a polymer melt instead of dissolving the polymer in a solvent as performed during solution electrospinning. The objective of this study was to investigate the significant parameters associated with the melt electrospinning process that influence fiber diameter and scaffold morphology, including processing temperature, collection distance, applied, voltage and nozzle size. The mechanical properties of these microfiber scaffolds varied with microfiber diameter. Additionally, the porosity of scaffolds was determined by combining experimental data with mathematical modeling. To test the cytocompatability of these fibrous scaffolds, we seeded neural progenitors derived from murine R1 embryonic stem cell lines onto these scaffolds, where they could survive, migrate, and differentiate into neurons; demonstrating the potential of these melt electrospun scaffolds for tissue engineering applications.

Towards high throughput tissue engineering: development of chitosan-calcium phosphate scaffolds for engineering bone tissue from embryonic stem cells.

Tissue engineering strategies have shown promise for the repair of damaged organs, including bone. One of the major challenges associated with tissue engineering is how to scale up such processes for high throughput manufacturing of biomaterial scaffolds used to support stem cell culture. Generation of certain types of 3D biomaterial scaffolds, including chitosan-calcium phosphate blends, involves a slow fabrication process followed by a lengthy required freeze drying step. This work investigates the use of automated microwave vacuum drying technology as an alternative to traditional freeze drying as a method of fabricating chitosan-calcium phosphate scaffolds for supporting embryonic stem cell cultures. Scaffolds produced using both drying techniques possess similar properties when characterized using scanning electron microscopy and this paper is the first to report that both types of these scaffolds support undifferentiated embryonic stem cell culture as well as promote stem cell differentiation into osteogenic lineages when treated with the appropriate factors. Compared to existing scaffold manufacturing processes using freeze drying, the use of microwave vacuum drying will lead to faster production times while reducing the costs, enabling high-throughput manufacturing of biomaterial scaffolds for stem cell applications.