Using sEMG Signal Frequency to Evaluate Post-Stroke Elbow Spasticity.

Spasticity is a motor disorder with high prevalence and critical consequences following a stroke. Reliable and sensitive measurements are important to guide the selection and evaluation of treatment strategies. Technology-assisted methods, such as the surface electromyography (sEMG) technique, have been developed to measure spasticity as sensitive and accurate alternatives to commonly used clinical scales. However, sEMG amplitude based measures may confound spasticity-induced muscle activities with other types of muscle contractions. This study thus introduces the idea of using sEMG frequency information to detect spasticity as a potential solution to overcome the limitations of existing sEMG based measures. The preliminary results of three patients demonstrate the possibility and future research directions for this approach.

Technology-assisted assessment of spasticity: a systematic review.

BACKGROUND: Spasticity is defined as "a motor disorder characterised by a velocity dependent increase in tonic stretch reflexes (muscle tone) with exaggerated tendon jerks". It is a highly prevalent condition following stroke and other neurological conditions. Clinical assessment of spasticity relies predominantly on manual, non-instrumented, clinical scales. Technology based solutions have been developed in the last decades to offer more specific, sensitive and accurate alternatives but no consensus exists on these different approaches. METHOD: A systematic review of literature of technology-based methods aiming at the assessment of spasticity was performed. The approaches taken in the studies were classified based on the method used as well as their outcome measures. The psychometric properties and usability of the methods and outcome measures reported were evaluated. RESULTS: 124 studies were included in the analysis. 78 different outcome measures were identified, among which seven were used in more than 10 different studies each. The different methods rely on a wide range of different equipment (from robotic systems to simple goniometers) affecting their cost and usability. Studies equivalently applied to the lower and upper limbs (48% and 52%, respectively). A majority of studies applied to a stroke population (N = 79). More than half the papers did not report thoroughly the psychometric properties of the measures. Analysis identified that only 54 studies used measures specific to spasticity. Repeatability and discriminant validity were found to be of good quality in respectively 25 and 42 studies but were most often not evaluated (N = 95 and N = 78). Clinical validity was commonly assessed only against clinical scales (N = 33). Sensitivity of the measure was assessed in only three studies. CONCLUSION: The development of a large diversity of assessment approaches appears to be done at the expense of their careful evaluation. Still, among the well validated approaches, the ones based on manual stretching and measuring a muscle activity reaction and the ones leveraging controlled stretches while isolating the stretch-reflex torque component appear as the two promising practical alternatives to clinical scales. These methods should be further evaluated, including on their sensitivity, to fully inform on their potential.

A Practical Post-Stroke Elbow Spasticity Assessment Using an Upper Limb Rehabilitation Robot: A Validation Study.

Spasticity is a motor disorder characterised by a velocity-dependent increase in muscle tone, which is critical in neurorehabilitation given its high prevalence and potential negative influence among the post-stroke population. Accurate measurement of spasticity is important as it guides the strategy of spasticity treatment and evaluates the effectiveness of spasticity management. However, spasticity is commonly measured using clinical scales which may lack objectivity and reliability. Although many technology-assisted measures have been developed, showing their potential as accurate and reliable alternatives to standard clinical scales, they have not been widely adopted in clinical practice due to their low usability and feasibility. This paper thus introduces an easy-to-use robotic based measure of elbow spasticity and its evaluation protocol. Preliminary results collected with one post-stroke patient and one healthy control subject are presented and demonstrate the feasibility of the approach.

A Weak Monotonicity Based Muscle Fatigue Detection Algorithm for a Short-Duration Poor Posture Using sEMG Measurements.

Muscle fatigue is usually defined as a decrease in the ability to produce force. The surface electromyography (sEMG) signals have been widely used to provide information about muscle activities including detecting muscle fatigue by various data-driven techniques such as machine learning and statistical approaches. However, it is well-known that sEMGs are usually weak signals with a smaller amplitude and a lower signal-to-noise ratio, making it difficult to apply the traditional signal processing techniques. In particular, the existing methods cannot work well to detect muscle fatigue coming from static poses. This work exploits the concept of weak monotonicity, which has been observed in the process of fatigue, to robustly detect muscle fatigue in the presence of measurement noises and human variations. Such a population trend methodology has shown its potential in muscle fatigue detection as demonstrated by the experiment of a static pose.

Effective Assessments of a Short-Duration Poor Posture on Upper Limb Muscle Fatigue Before Physical Exercise.

A forward head and rounded shoulder posture is a poor posture that is widely seen in everyday life. It is known that sitting in such a poor posture with long hours will bring health issues such as muscle pain. However, it is not known whether sitting in this poor posture for a short period of time will affect human activities. This paper investigates the effects of a short-duration poor posture before some typical physical activities such as push-ups. The experiments are set up as follows. Fourteen male subjects are asked to do push-ups until fatigue with two surface electromyography (sEMG) at the upper limb. Two days later, they are asked to sit in this poor posture for 15 min with eight sEMG sensors located at given back muscles. Then they do the push-ups after the short-duration poor posture. The observations from the median frequency of sEMG signals at the upper limb indicate that the short-duration poor posture does affect the fatigue procedure of push-ups. A significant decreasing trend of the performance of push-ups is obtained after sitting in this poor posture. Such effects indicate that some parts of the back muscles indeed get fatigued with only 15 min sitting in this poor posture. By further investigating the time-frequency components of sEMG of back muscles, it is observed that the low and middle frequencies of sEMG signals from the infraspinatus muscle of the dominant side are demonstrated to be more prone to fatigue with the poor posture. Although this study focuses only on push-ups, similar experiments can be arranged for other physical exercises as well. This study provides new insights into the effect of a short-duration poor posture before physical activities. These insights can be used to guide athletes to pay attention to postures before physical activities to improve performance and reduce the risk of injury.

A facile synthesis of hierarchically porous carbon derived from serum albumin by a generated-templating method for efficient oxygen reduction reaction.

Hierarchically porous carbons (HPCs), with large specific surface area, abundant porous channels and adequate anchor points, act as one type of ideal carbon supports for the preparation of single-atom electrocatalysts. In this study, the blood plasma-derived HPC with an interconnected porous framework is constructed via a generated-template method, with the formation of ZnS nanoparticles from the abundant disulfide bonds (-S-S-) in serum albumin. After the thermal activation with heme-containing molecules (also from the bovine-blood biowaste), the HPC exhibits high-exposure and low-spin-state Fe(ii)-N4 atomic active sites, and thereby presents a superior oxygen reduction reaction activity (the half wave potential of 0.87 V) and excellent stability (a 4 mV negative shift after 3000 potential cycles), even comparable with the benchmark Pt/C. This work delivers a new insight into the design and synthesis of porous carbons and carbon-based electrocatalysts to develop bio-derived materials in the field of clean energy conversion and storage.