Muscle Strength

Currently there is no consensus on the most appropriate testing positions for HHD use, with a recent systematic review demonstrating a variety of methodologies used for lower limb assessment in previous research [25 (link)]. Based on prior research and our own pilot work of assessments in a variety of different positions, we implemented those shown in Fig 1. These testing positions have shown strong reliability for the measurement of isometric strength in previous studies for the hip [36 (link)], knee [37 (link)], and ankle [37 (link)] muscle groups.
Assessment of isometric muscle strength and power was performed with the participants in three positions (seated, supine, and prone); hip flexors, knee extensors, and knee flexors were assessed in a seated position; ankle plantarflexors, ankle dorsiflexors, hip abductors, and hip adductors in a supine position; hip extensors in a prone position. These positions were chosen to minimise changes in position by the participant to enhance the feasibility of testing in a clinical setting. All tests involved maximal voluntary isometric contractions. Assessment using the HHDs was conducted first. The order was randomised for assessor and HHD, however the order of the muscle groups tested was kept consistent as shown in Fig 1; for example if HHD1 was randomly assigned first, all seated muscle groups would be assessed, followed by HHD2 assessing seated muscle groups, with the same order of HHDs for supine and then prone muscle groups. Following a rest period of five minutes, the same protocol was repeated by the second assessor. During pilot testing, problems arose in the assessment of very strong muscle groups, namely the knee extensors and ankle plantarflexors. To assist the assessor in overcoming the force produced by the participant, the plinth was placed close to a wall, which aided the assessors in their resistance of the participants’ contractions for these two muscle groups (see Fig 1B and 1D).
Following HHD testing, the isometric strength and power of participants was then assessed using the KinCom dynamometer utilising the positions described for the HHDs. In order to minimise position changes and reduce time requirements, the order of muscles tested was different during the assessment with the KinCom dynamometer. The order for the KinCom was as follows: knee extensors, knee flexors, hip flexors, hip abductors, hip adductors, hip extensors, ankle plantarflexors, and ankle dorsifexors. Instructions provided to participants for all trials were ‘at the count of three, push/pull as hard and as fast as you can and hold that contraction until I say relax’. Each test lasted between three to five seconds and ended after a steady maximal force was produced by the participant. Participants were instructed to hold the side of the plinth for stabilization (see Fig 1). Constant verbal encouragement was provided throughout the testing. Only the right limb of each participant was assessed to reduce fatigue and the time demands of the testing session. A submaximal practice trial was given for each muscle group on both HHDs and the fixed dynamometer to ensure the participant understood the contraction required. Two trials were recorded for each muscle group, again to minimise the time requirements of testing.

This paper presents a re-analysis of data we reported previously (Hipp et al., 2011 (link)). We recorded the continuous EEG from 126 scalp sites and the electrooculogram (EOG) from two sites below the eyes all referenced against the nose tip (sampling rate: 1000 Hz; high-pass: 0.01 Hz; low-pass: 250 Hz; Amplifier: BrainAmp, BrainProducts, Munich, Germany; Electrode cap: Electrodes: sintered Ag/AgCl ring electrodes mounted on an elastic cap, Falk Minow Services, Herrsching, Germany). Electrode impedances were kept below 20 kΩ. Offline, the data were high-pass filtered (4 Hz, Butterworth filter of order 4) and cut into trials of 2.5 s duration centered on the presentation of the sound (−1.25 to 1.25 s). First, trials with eye movements, eye blinks, or strong muscle activity were identified by visual inspection and rejected from further analysis (trials retained for further analyses n = 345 ± 50, mean ± s.d.). Next, we used independent component analysis (FastICA, http://www.cis.hut.fi/projects/ica/fastica/; Hyvärinen, 1999 (link)) to remove artifactual signal components (Jung et al., 2000 (link); Keren et al., 2010 (link)). The removed artifactual components constituted facial muscle components (n = 45.8 ± 7.84, mean ± s.d.), microsaccadic artifact components (n = 1.2 ± 0.82, mean ± s.d.), auricular artifact components (O'Beirne and Patuzzi, 1999 (link)) (n = 0.5 ± 0.83, mean ± s.d.), and heart beat components (n = 0.5 ± 0.59, mean ± s.d.). Alternatively to ICA, we accounted for microsaccadic artifacts by removing confounded data sections identified in the radial EOG using the approach and template described in Keren et al. (2010 (link)) (Threshold: 3.5). Importantly, for this analysis step, we did not reject entire trials containing a microsaccadic artifact (79 ± 18%, mean ± s.d., of trials contained at least one saccadic spike artifact), but only invalidated the data in the direct vicinity of detected artifacts (±0.15 s). Whenever the window for time-frequency transform overlapped with invalidated data (see spectral analysis below), it was rejected from further analysis. As a consequence, spectral estimates were based on varying amount of data across time and frequency. We derived the radial EOG as the difference between the average of the two EOG channels and a parietal EEG electrode at the Pz position of the 10–20-system. Notably, rejection based on the radial EOG may miss saccadic spike artifacts of small amplitude that can be detected with high-speed eyetracking (Keren et al., 2010 (link)). However, the fact that we did not find any significant saccadic spike artifacts after radial EOG based rejection at those source locations that before cleaning best captured these artifacts (cf. Figure 7C) suggests that potentially remaining artifacts are small.

To derive the cut-off values used for the sarcopenia definition with reference to the presented values of AWGS [5 (link)], the muscle mass value was obtained by dividing the sum of the limbs’ muscle mass by the square of height of the skeletal muscle mass index (SMI): 7.0 kg/m² for men and 5.4 kg/m² for women. The cutoff for grip strength in men was 26 kg and in women it was 18 kg, and a 6 m walking speed of 0.8 m/sec was set as the cutoff for both men and women. We defined sarcopenia as the presence of both low muscle function (low physical performance or low muscle strength) and low muscle mass.
We used the components identified by Freid et al. [20 (link)] for frailty: (1) shrinking: measured as weight loss; (2) weakness: measured as grip strength; (3) poor endurance and energy: measured by questionnaires; (4) slowness: measured as decreased walking speed and (5) low physical activity level: measured by questionnaires, defined as endorsing three or more items. Incidentally, the cut-off values for grip strength and walking speed were the same as those for sarcopenia.
To define dynapenia we used cut-off values that included isometric knee extension strength of 18.0 kg in men 16.0 kg in women. The values were calculated as described by Assantachai et al. [21 (link)], who monitored 2149 men and women over 60 years of age for a period of 2 years.
The cut-off value for UST was set to 30 s; this has been reported by Hurvitz et al [17 (link)] to be useful for fall prediction. We defined “static balance disorder” as UST less than 30 s.

Seventy-seven patients aged ≥ 65 years old with similar diet and environmental conditions in the Second Xiangya Hospital of Central South University were enrolled in this study. Patients were classified into the following 3 categories: 33 HF patients without sarcopenia (HF group), 29 HF patients with sarcopenia (SHF group), and 15 control individuals (Control group). Sarcopenia was diagnosed according to the Asian Working Group for Sarcopenia 2019 Guidelines (Chen et al., 2020 (link)). Low skeletal muscle mass was defined as muscle mass < 7.0 kg/m² (male) or < 5.7 kg/m² (female) by bioelectrical impedance analysis using the InBodyS10 body composition analyzer (Chen et al., 2014 (link)). Low muscle strength was defined as handgrip strength <28 kg for male and <18 kg for female. Criteria for low physical performance is a 6-m walk speed < 1 m/s. Sarcopenia was defined as low muscle mass plus either diminished muscle strength or physical performance. Exclude subjects included recurrent diarrhea or constipation, unusual dietary habits (vegetarians), edema, those with tumors, diabetes, intestinal inflammation, irritable bowel syndrome, history of intestinal surgery, being treated with antibiotics or probiotics within 1 month. Demographic characteristics and clinical laboratory examinations were documented for all patients. The study was approved by the local Ethics Committee of the Second Xiangya Hospital of Central South University. Written informed consent was obtained from all participants. This study was conducted under the Declaration of Helsinki.

This test was used to evaluate muscle strength of the forelimbs. The mouse was lowered over a grid and permitted to grip the top portion of the grid with its forepaws. The mouse was gently pulled from the grid by its tail. Grip strength was represented as the g-force required for the mouse to release its grip on the grid. This procedure was repeated 3 times and the mean grip strength was calculated for that session.