Lasse Schlör
lasse-schloer@unibo.it

MMM SB & GA meeting
2025-09-15

DC8 / WP3.1:
Individually tailored digital-
motor outcomes in real life
Research progress

University of Bologna logo mHealth Technologies logo Medicine Made to Measure logo
EU flag

Funded by the European Union’s Horizon Europe Marie Skłodowska-Curie Actions scheme, GA no. 101120256.

Supervisors

Dr. Sabato Mellone
Dr. Sabato Mellone
University of Bologna
Matthis Synofzik
Prof. Dr. Matthis Synofzik
University of Tübingen
Prof. Dr. Mats Karlsson
Prof. Dr. Mats Karlsson
University of Uppsala
Carlo Tacconi
Carlo Tacconi
mHealth Technologies s.r.l., Bologna
Prof. Dr. Lorenzo Chiari
Prof. Dr. Lorenzo Chiari
University of Bologna

Gait feature extraction summary figure

Gait feature extraction

Deliverables

D3.1 Outcomes of the large cohort study
Completed Jan 2025
D3.2 Outcomes of focused study
Due May 2027 (postponed)
D3.3 Robust capture of n-of-1 movement changes
Due Sep 2027

D3.1 (large cohort study)

outcome ess rb_lgt rb_crs ρ_ΔΔ_2y spread
1y 2y 3y sym sara<8 sara≥8 sara -abc
test_dw_instance_compound_5 39 .86 .75 .96 .68 .28 .67 .32 .12
test_dw_instance_compound_3 45 .82 .66 .93 .59 .18 .62 .26 .26
test_dw_instance_compound_2 55 .77 .78 .78 .49 .36 .48 .58 .21
test_dw_instance_compound_4 66 .79 .65 .36 .75 .48 .52 .33 .2
agg_adjacent_swings_resampled_sensor_lumbar_acc_x_r_d1_abs_μ /σ /curvy_long/μ 74 .71 .45 .76 .52 .32 .46 -.5 -.06 .47
agg_adjacent_swings_resampled_sensor_lumbar_acc_x_r_μ /σ /curvy_long/μ 83 .62 .62 .67 .54 .24 .45 -.32 .0055 .45
agg_adjacent_swings_resampled_sensor_lumbar_gyr_z_r_abs_μ /σ /long /μ 86 .68 .46 .54 .5 .066 .42 -.036 .2 .52
agg_adjacent_swings_resampled_sensor_lumbar_gyr_z_r_abs_d1_abs_μ/σ /long /μ 88 .72 .4 .41 .49 .09 .4 .062 .32 .57
agg_adjacent_swings_resampled_sensor_lumbar_acc_x_r_abs_μ /σ /curvy_long/μ 88 .58 .66 .65 .54 .24 .45 -.3 .21 .42
agg_adjacent_swings_resampled_sensor_lumbar_gyr_z_r_abs_d3_abs_μ/σ /long /μ 89 .71 .42 .38 .48 .067 .41 .11 .093 .54
stance_duration_μ /cv/curvy_long/μ 90 .65 .76 .38 .63 .29 .52 .25 -.43 .45
agg_adjacent_swings_resampled_sensor_lumbar_gyr_z_r_abs_d2_abs_μ/σ /long /μ 93 .71 .44 .38 .48 .067 .4 .11 .21 .54
agg_adjacent_swings_resampled_sensor_lumbar_gyr_z_r_abs_d1_abs_μ/μ /long /μ 94 .62 .52 .43 .54 .12 .42 .16 .31 .44
double_support_apdm_μ /σ /curvy_long/μ 95 .69 .46 .49 .72 .42 .46 .13 -.37 .36
coeff_swings_sensor_acc_dft_x_1_abs_μ /cv/long /μ 95 .76 .51 .43 .71 .43 .44 .1 .044 .41
agg_adjacent_swings_resampled_sensor_lumbar_acc_x_r_abs_d2_abs_μ/μ /curvy_long/μ 96 .66 .5 .56 .63 .32 .49 -.24 .088 .42
agg_adjacent_swings_resampled_sensor_lumbar_gyr_z_r_abs_d3_abs_μ/μ /long /μ 97 .65 .49 .43 .54 .12 .42 .24 .35 .46
swing_apdm_μ /cv/curvy_long/μ 98 .72 .58 .49 .7 .36 .51 .15 -.32 .36
agg_adjacent_swings_resampled_sensor_lumbar_gyr_z_r_abs_d2_abs_μ/μ /long /μ 98 .64 .51 .41 .53 .11 .42 .22 .31 .43
agg_adjacent_swings_resampled_sensor_lumbar_acc_z_r_abs_d3_abs_μ/γ /short /μ 98 -.69 -.53 -.41 -.48 -.28 -.48 -.57 -.15 .69
agg_adjacent_swings_resampled_sensor_lumbar_acc_x_r_abs_d1_abs_μ/σ /curvy_long/μ 100 .66 .45 .69 .51 .31 .44 -.49 .071 .42
initial_plus_mid_swing_apdm_μ /cv/curvy_long/μ 100 .63 .69 .6 .67 .42 .42 -.097 .082 .38
agg_adjacent_swings_resampled_sensor_lumbar_gyr_z_r_abs_μ /cv/long /μ 100 .57 .56 .47 .5 .072 .41 .1 .15 .57
gait_speed_apdm_μ /σ /curvy_long/μ 100 .57 .73 .34 .44 .21 .45 .39 0 .42
(…)
sara_sim_1 103 .53 .56 .76 1 .85 1 1 .077
(…)

D3.2 (focused study)

Postponed:

D3.3 (n-of-1)

In progress:
1. Outcome pre-selection
  • D3.1 results, continually refined
  • Machine learning (e.g. random forest)
2. Cross-sectional latent disease severity model
  • Relate outcomes to true disease severity
  • Further narrow down most informative outcomes
3. Longitudinal disease progression model
  • Predict untreated disease course
  • Estimate trial parameters

Secondments

Bologna, Tübingen, and Uppsala
  • Uppsala, Sweden
    • Aug 2025 - Sep 2025
  • Tübingen, Germany
    • Sep 2024 - Nov 2024
    • Three more months in the coming years

Training & conferences

Thank you!

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