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Recent advances in small inexpensive sensors, low-power processing, and activity modeling have enabled applications that use on-body sensing and machine learning to infer people's activities throughout everyday life. To address the growing rate of sedentary lifestyles, we have developed a system, UbiFit Garden, which uses these technologies and a personal, mobile display to encourage physical activity. We conducted a 3-week field trial in which 12 participants used the system and report findings focusing on their experiences with the sensing and activity inference. We discuss key implications for systems that use on-body sensing and activity inference to encourage physical activity.

AimTo investigate the respective influence of software tool and total metabolic tumor volume (TMTV0) calculation method on prognostic stratification of baseline 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography ([18F]FDG-PET) in newly diagnosed Hodgkin lymphoma (HL).Methods59 patients with newly diagnosed HL were retrospectively included. [18F]FDG-PET was performed before any treatment. Four sets of TMTV0 were calculated with Beth Israel (BI) software: based on an absolute threshold selecting voxel with standardized uptake value (SUV) >2.5 (TMTV02.5), applying a per-lesion threshold of 41% of the SUVmax (TMTV041) and using a per-patient adapted threshold based on SUVmax of the liver (>125% and >140% of SUVmax of the liver background; TMTV0125 and TMTV0140). TMTV041 was also determined with commercial software for comparison of software tools. ROC curves were used to determine the optimal threshold for each TMTV0 to predict treatment failure.ResultsMedian follow-up was 39 months. There was an excellent correlation between TMTV041 determined with BI and with the commercial software (r = 0.96, p<0.0001). The median TMTV0 value for TMTV041, TMTV02.5, TMTV0125 and TMTV0140 were respectively 160 (used as reference), 210 ([28;154] p = 0.005), 183 ([-4;114] p = 0.06) and 143ml ([-58;64] p = 0.9). The respective optimal TMTV0 threshold and area under curve (AUC) for prediction of progression free survival (PFS) were respectively: 313ml and 0.70, 432ml and 0.68, 450ml and 0.68, 330ml and 0.68. There was no significant difference between ROC curves. High TMTV0 value was predictive of poor PFS in all methodologies: 4-years PFS was 83% vs 42% (p = 0.006) for TMTV02.5, 83% vs 41% (p = 0.003) for TMTV041, 85% vs 40% (p<0.001) for TMTV0125 and 83% vs 42% (p = 0.004) for TMTV0140.ConclusionIn newly diagnosed HL, baseline metabolic tumor volume values were significantly influenced by the choice of the method used for determination of volume. However, no significant differences were found in term of prognosis.