Jem Arnold

A visual analogy for why small changes in #NIRS probe position can return considerably different signals - chaotic scattering & absorption within tissue Mostly it averages out, but differential pathlength factor DPF is fundamentally unstable, while CW-NIRS assumes it's fixed (1/2)

Muscle oxidative capacity analysis with #mnirs is monoexponential by consensus. But are there secondary drift kinetics hiding in the data and biasing results?🤔 No idea, but could 'slow-component' drift be related to hyperaemia + metabolic rate adjustments as seen here? Thoughts? #rstats

{mnirs} R package for reading, processing, analysing muscle near-infrared spectroscopy data🦵🔦 updated to 0.7.0 Mostly internal performance improvements getting ready for `mnirs::analyse_kinetics()` soon! github.com/jemarnold/mn... Here are the key changes: 1/5🧵🔗👇 #rstats #nirs #muscleoxygenation

4/5 A minor ⚠️ breaking change to `shift_mnirs()`, `replace_mnirs()`, and `extract_intervals()`: `group_channels` arg handles channels `group_intervals` arg handles intervals for `extract_intervals()` Options are “distinct”, “ensemble”, or a custom group list

{mnirs} R package for reading, processing, analysing muscle near-infrared spectroscopy data🦵🔦 updated to 0.7.0 Mostly internal performance improvements getting ready for `mnirs::analyse_kinetics()` soon! github.com/jemarnold/mn... Here are the key changes: 1/5🧵🔗👇 #rstats #nirs #muscleoxygenation

2/5 Core processing functions now accept a list of data frames or grouped dfs with `dplyr::group_by()`: You can `filter_mnirs()` over a list of dfs from multiple `read_mnirs()` files Or `extract_intervals()` from a longer session and `rescale_mnirs()` each independently

Another call for input! 📢 CLINICIANS, COACHES, and ATHLETES managing recovery from surgery for flow limitations in the iliac artery FLIA / endofibrosis We'd love to hear your experiences to help improve care for athletes. Please contact email below 👇 #cycling #sportsmedicine #sportmedicine

How long does it take for blood to make a full round-trip around the entire body during exercise? 🫁🫀🔁🦵 Only 10-sec! That’s way faster than I intuitively would have expected But we’re just reproducing what’s been known for the last century👇 #science #medicine #rstats #datavis

This paper found similar ~11sec mean recirculation time in females & males treadmill walking at 3 mph (12:25/km) @ 5% grade So already at walking intensity, or cycling near V̇O₂max, bulk blood flow velocity is nearly the same?😮 Chapman & Fraser 1954 doi.org/10.1161/01.C...

This is how we can resample breath-by-breath metabolic data to 1 Hz using `mnirs::resample_mnirs()` The secret is {mnirs} works on many time series data, not just NIRS 🤫 #rstats #nirs #cpet

. @fredrikmentzoni.bsky.social here is that sensitivity analysis on smoothing levels for BxB Tymewear vs Parvo respiration rate Methods are un-smoothed; moving-avg by breath; moving-avg by time, and binned by time (reduce to single mean sample per bin)

I was just reminded of this nice test-retest reliability study for intensity at #Fatmax & fat oxidation (g/min) This week are we the red line or the blue line? How about next week?? 🤷‍♂️ Fatmax can be useful, but it isn't magic 🧙‍♂️ pubmed.ncbi.nlm.nih.gov/32488584/

Always important to consider how relevant & valid are physiological tests to predict real-world training targets / performance outcome If we want to maximise FatOx in a training session, we can do so in a wide intensity range. FatMax isn't magic 🧙‍♂️ pubmed.ncbi.nlm.nih.gov/24022578/

I was just reminded of this nice test-retest reliability study for intensity at #Fatmax & fat oxidation (g/min) This week are we the red line or the blue line? How about next week?? 🤷‍♂️ Fatmax can be useful, but it isn't magic 🧙‍♂️ pubmed.ncbi.nlm.nih.gov/32488584/

To add a bit more context, this excellent review summarises all the different operational decisions (methodological differences) that influence results when testing for FatMax under laboratory conditions pubmed.ncbi.nlm.nih.gov/30929281/

Quick update {mnirs} 🦵🔦 0.6.3 pushed to CRAN Main improvement with plotting lists of data frames as facets, primarily for extracted intervals Here is how you can extract intervals by time values from data processed with #mnirs, for subsequent analysis (kinetics analysis coming soon🤞) #rstats #nirs

Just updated {mnirs} 🦵🔦 app with interactive Plotly for improved no-code workflow processing #muscleoxygenation #nirs #rstats data! Access here: jemarnold-mnirs-app.share.connect.posit.cloud 🔎 Pan & zoom to explore precise time scales 📈️ Compare effects of filtered vs raw tracings A bit more 🧵👇

What looks like noise at a wide timescale in this cycling interval (recorded at 10Hz w/ @artinis.bsky.social) is actually meaningful intra-cadence changes in Oxy[haeme] Zooming in on the occlusion, we see distortion caused by over-parameterising the Butterworth filter order

Garmin sounds serious about #muscleoxygenation #mnirs. "Muscle Battery" gives me high hopes and cautious expectations 😄 What do you think?🤔 Very interested to see how they solve the hardware distribution problem, and how the model learns from repeated measurements

I don't use "body battery" myself, but I appreciate it's a first step into training load/stress monitoring. "Muscle battery" will likely be similar More advanced athletes will of course interpret it within greater context gained from experience