Torque Onset Angle of the Knee Extensor as a Predictor of Walking Related Balance in Stroke Patients

Objective@#To investigate the relationship between the torque onset angle (TOA) of the isokinetic test for knee extensors in the paretic side and walking related balance in subacute stroke patients. @*Methods@#We retrospectively reviewed patients with first-ever strokes who have had at least two isokinetic tests within 6 months of onset. 102 patients satisfied the inclusion criteria. The characteristics of walking related balance were measured with the Berg Balance Scale sub-score (sBBS), Timed Up and Go test (TUG), 10-m Walk Test (10MWT) and Functional Independence Measure sub-score (sFIM). The second isokinetic test values of the knee extensor such as peak torque, peak torque to weight ratio, hamstring/quadriceps ratio, TOA, torque stop angle, torque at 30 degrees, and peak torque asymmetry ratio between paretic and non-paretic limb were also taken into account. Pearson’s correlation, simple regression and multiple regression analysis were used to analyze the correlation between TOA and walking related balance. @*Results@#TOA of the knee extensor of the paretic limb showed significant correlations with BBS, sBBS, TUG, 10MWT, and sFIM according to Pearson’s correlation analysis. TOA also had moderate to good correlations with walking related balance parameters in partial correlation analysis. In multiple regression analysis, TOA of the paretic knee extensor was significantly associated with walking related balance parameters. @*Conclusion@#This study demonstrated that TOA of the paretic knee extensor is a predictable parameter of walking related balance. Moreover, we suggest that the ability to recruit muscle quickly is important in walking related balance.

Effect of Antigravity Treadmill Gait Training on Gait Function and Fall Risk in Stroke Patients

Objective@#To investigate the effect of antigravity treadmill gait training (AGT) on gait function, balance, and fall risk in stroke patients. @*Methods@#This study included 30 patients with stroke (mean age, 73 years). All subjects were randomly divided into two groups. The intervention group (n=15) performed AGT for 20 minutes, five times per week for 4 weeks. The control group (n=15) received conventional gait training for the same duration. To assess fall risk, the Tinetti Performance-Oriented Mobility Assessment (POMA) was measured. The Berg Balance Scale (BBS), Timed Up and Go test (TUG), and 10-m walk test (10mWT) were measured to assess dynamic balance. All scales were measured before intervention (T0) and at 4 weeks (T1) and 12 weeks (T2) after intervention. @*Results@#Results showed that the total POMA score, BBS, and 10mWT scores improved significantly (p<0.05) at T1 and T2 in both groups. The POMA gait score (4.20±1.37 at T1, 4.87±1.36 at T2) and TUG (4.52±4.30 at T1, 5.73±4.97 at T2) significantly improved (p<0.05) only in the intervention group. The changes in total POMA score and BBS of the intervention group (7.20±2.37, 7.47±3.07) improved more significantly (p<0.05) between T0 and T2 than the control group (2.53±2.10, 2.87±2.53). @*Conclusion@#Our study showed that AGT enhances dynamic balance and gait speed and effectively lowers fall risk in stroke patients. Compared to conventional gait therapy, AGT would improve gait function and balance in stroke patients more effectively.

Wearable bio signal monitoring system applied to aviation safety.

Pilots are required to have the ability to evaluate their own physical and psychological status to operate high performance aircrafts effectively. Existing studies have lacked consideration of applying bio signal of pilots in real time flight situation. The purpose of this study is to develop a wearable bio signal monitoring system that can measure the condition of pilots under an extreme flight environment to ensure flight safety. The wearable bio signal monitoring system consists of an algorithm for evaluating pilots' physiological stability, algorithms for detecting Gravity-induced Loss of Consciousness (G-LOC) prognosis, pilots' interaction module, and pilots' context awareness platform. The algorithm for evaluating pilots' physiological stability uses psychomotor cognitive test (PCT) and heart rate variability (HRV) to measure pilots' mission performance before flight. The algorithms for detecting G-LOC prognosis utilizes electromyogram (EMG) to generate warning signal during flight. The pilots' interaction module was developed for pilots to operate the system efficiently under flight environment. The pilots' context awareness platform was designed for the system to process multiple sensor signals in real time. This wearable bio signal monitoring system is expected to enhance flight safety and mission performance of pilots.

Search for Structural Cardiac Abnormalities Following Sudden Cardiac Arrest Using Post-mortem Echocardiography in the Emergency Department: A Preliminary Study

PURPOSE: Sudden cardiac arrest (SCA) accounts for approximately 15% of all-cause mortality in the US and 50% of all cardiovascular mortalities in developed countries; 10% of cases have an underlying structural cardiac abnormality. An echocardiography has widely been used to evaluate cardiac abnormality, but it needs to be performed by emergency physicians available in the emergency department immediately after death, rather than by cardiologists. We aimed to determine whether post-mortem echocardiography (PME) performed in the emergency department may reveal such abnormalities. METHODS: We evaluated the reliability and validity of PME performed by emergency physicians in the emergency department. Measurement by a cardiologist was used as reference. RESULTS: Two emergency physicians performed PME on 3 out of the 4 included patients who died after unsuccessful cardiopulmonary resuscitation. PME was started within 10 minutes of death, and it took 10 minutes to complete. Parasternal views in either supine or left decubitus position were most helpful. The adequacy of the image was rated good to fair, and that of measurements was acceptable to borderline. Regarding the chamber size and left ventricular wall thickness, intraclass correlation coefficients for reliability and validity were 0.97 (n=15) and 0.95 (n=35), respectively (p<0.001). Evaluation of presence/absence of left ventricular wall thinning, valve calcification, and pericardial effusion was incomplete (3/7-5/7), precluding further analysis. CONCLUSION: Emergency physicians could perform reliable and valid PME to assess the chamber size and left ventricular wall thickness. A large prospective study with collaboration between emergency physicians and cardiologists would reveal the feasibility and usefulness of PME in diagnosing structural causes of sudden cardiac arrest.

Detection of G-Induced Loss of Consciousness (G-LOC) prognosis through EMG monitoring on gastrocnemius muscle in flight.

G-Induced Loss of Consciousness (G-LOC) is mainly caused by the sudden acceleration in the direction of +Gz axis from the fighter pilots, and is considered as an emergent situation of which fighter pilots are constantly aware. In order to resist against G-LOC, fighter pilots are subject to run Anti-G straining maneuver (AGSM), which includes L-1 respiration maneuvering and muscular contraction of the whole body. The purpose of this study is to create a G-LOC warning alarm prior to G-LOC by monitoring the Electromyogram (EMG) of the gastrocnemius muscle on the calf, which goes under constant muscular contraction during the AGSM process. EMG data was retrieved from pilots and pilot trainees of the Korean Air Force, during when subjects were under high G-trainings on a human centrifugal simulator. Out of the EMG features, integrated absolute value (IAV), reflecting muscle contraction, and waveform length (WL), reflecting muscle contraction and fatigue, have shown a rapid decay during the alarm phase, 3 seconds before G-LOC, compared to that of a normal phase withstanding G-force. Such results showed consistency amongst pilots and pilot trainees who were under G-LOC. Based on these findings, this study developed an algorithm which can detect G-LOC prognosis during flight, and at the same time, generate warning signals. The probability of G-LOC occurrence is detected through monitoring the decay trend and degree of the IVA and WL value of when the pilot initiates AGSM during sudden acceleration above 6G. Conclusively, this G-LOC prognosis detecting and warning system is a customized, real-time countermeasure which enhanced the accuracy of detecting G-LOC.