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Objective Resources for management of epilepsy in Africa are extremely limited reinforcing the need to develop innovative strategies for optimizing care. Studies have shown that the prevalence of epilepsy in low‐ and middle‐income countries is substantially greater than in more resourced countries. The objective of this report was to demonstrate that mobile Health (mHealth) technologies have the potential to improve the management of epilepsy in Africa. Methods The feasibility of technology‐based home monitoring was investigated in an observational study of 40 children with refractory epilepsy or epilepsy associated with intellectual disability and/or behavior difficulties in South Africa. Technology‐based home monitoring was implemented for six months. Physical activity, sleep, and heart rate were continuously monitored with a wearable device. Caregivers completed regular mobile Patient Reported Outcomes (mPROs) and reported seizures and ad hoc events using a dedicated app. Feasibility was assessed and descriptively measured for recruitment, retention, and engagement of the participants. Results The mHealth technology was able to capture important information that gives an impression of the overall experience of the children and their caregivers. Thirty‐seven participants (94.9%) reported at least one clinical event. Seventy‐nine percent of caregivers reported seizure events in their children, which were the primary event anticipated. Median engagement with the wearable device and monthly mPROs was 30.8% and 57.1%, respectively. However, most participants (87%) had to be given smartphones for them to have Bluetooth capabilities and access to the study app. Tolerability to the device was impacted by the difficult living circumstances of caregivers that induced fear of loss or theft. Significance The study showed how the use of remote patient monitoring in the form of mHealth can benefit epilepsy patients, despite highly variable engagement with the technology. The combination of mPROs and wearable devices generated informative datasets that will allow clinicians but also the children and their caregivers to better understand and manage the disease.

Background Up to 70% of individuals diagnosed with adult-onset idiopathic focal cervical dystonia (AOIFCD) report difficulties with sleep. Larger cohort studies using wrist-worn accelerometer devices have emerged as an alternative to smaller polysomnography studies, in order to evaluate sleep architecture. Methods To measure activity during the sleep/wake cycle, individuals wore a consumer-grade wrist device (Garmin vivosmart 4) continuously over 7 days on their non-dominant wrist, while completing a daily sleep diary and standardised sleep and non-motor questionnaires via a dedicated app. Sleep measures were derived from the captured raw triaxial acceleration and heart rate values using previously published validated algorithms. Results Data were collected from 50 individuals diagnosed with AOIFCD and 47 age- and sex-matched controls. Those with AOIFCD self-reported significantly higher levels of excessive daytime sleepiness (p = 0.04) and impaired sleep quality (p = 0.03), while accelerometer measurements found the AOIFCD cohort to have significantly longer total sleep times (p = 0.004) and time spent in NREM sleep (p = 0.009), compared to controls. Overall, there was limited agreement between wearable-derived sleep parameters, and self-reported sleep diary and visual analogue scale records. Discussion This study shows the potential feasibility of using consumer-grade wearable devices in estimating sleep measures at scale in dystonia cohorts. Those diagnosed with AOIFCD were observed to have altered sleep architecture, notably longer total sleep time and NREM sleep, compared to controls. These findings suggest that previously reported disruptions to brainstem circuitry and serotonin neurotransmission may contribute to both motor and sleep pathophysiology.

Background and aim\ud The evaluation of patient-reported outcomes (PRO) in cancer has proven relevant positive clinical impact on patients’ communication with healthcare professionals, decision-making for management, well-being, and overall survival. However, the optimal frequency of PRO assessment has yet to be defined. Based on the assumption that more frequent sampling would enhance accuracy, we aimed at identifying the optimal sampling frequency that does not miss clinically relevant insight.\ud \ud Methods\ud We used pilot data from 31 advanced cancer patients who completed once daily the 19-item MD Anderson Symptom Inventory at home. The resulting dataset allowed us to compare different PRO assessment frequencies to daily sampling, i.e., alternate days (q2d), every third day (q3d), or once a week (q1w). We evaluated the sampling frequencies for two main outcomes: average symptom intensity and identification of severe symptoms.\ud \ud Results\ud The majority of the differences between corresponding averages of daily data and those for q2d, q3d, and q1w datasets were close to 0, yet the extremes exceeded 5. Clinically meaningful differences, i.e., > 1, were observed in 0.76% of patient items for q2d, in 2.72% for q3d, and in 11.93% for q1w. Moreover, median values of missed instances of a severe symptom (i.e., > 6) were 14.6% for q2d, 27.8% for q3d, and 55.6% for q1w.\ud \ud Conclusions\ud Our analysis suggests that in patients receiving chemotherapy for advanced cancer, increasing the density of PRO collection enhances the accuracy of PRO assessment to a clinically meaningful extent. This is valid for both computations of averages symptom burden and for the recognition of episodes of severe symptom intensity.

UNSTRUCTURED The administration of treatments according to circadian rhythms (chronotherapy) aims at advancing precision medicine through tailoring health care and drug delivery to the patients’ biological clocks. The objective of this paper is to present the IoT platform ‘Clinikali’. ‘Clinikali’ is the first-of-its kind IoT mobile platform of artificial intelligence-assisted home care that we develop, conceptualized as domomedicine. Multidimensional telemonitoring of rest-activity and body temperature circadian rhythms, sleep, and physical activity, jointly with subjective symptoms and quality of life is implemented through wireless BLE sensors and electronic tablets connected via GPRS to the ‘Clinikali’ platform server. Parameters are automatically computed in real time. Alerts are generated whenever threshold values are bypassed. A graphical user interface allows for data and parameters dynamics to be seen by health professionals. Feasibility, compliance and reliability are validated in a field test. The domomedicine platform is currently implemented in the MultiDom trial (NCT04263948), for improving outcomes in frail pancreatic cancer patients receiving chemotherapy. Gathering real time information on individual patients’ circadian rhythms and symptoms generates sensitive early warning signals in order to enhance safety through triggering proactive interventions. Quantitative measures of circadian biomarkers further provide cues for the personalization of chronotherapy. Such domomedicine platform should also help improving outcomes in patients with chronic or infectious diseases, which account for most human mortality.

Background\ud \ud Psychosocial symptoms often cluster together, are refractory to treatment, and impair health‐related quality of life (HR‐QoL) in cancer patients. The contribution of circadian rhythm alterations to systemic symptoms has been overlooked in cancer, despite a causal link shown under jet lag and shift work conditions. We investigated whether the circadian rest‐activity rhythm provides a reliable and objective estimate of the most frequent patient‐reported outcome measures (PROMs).\ud \ud Methods\ud \ud Two datasets were used, each involving concomitant 3‐day time series of wrist actigraphy and HR‐QoL questionnaires: EORTC QLQ‐C30 was completed once by 237 patients with metastatic colorectal cancer; MD Anderson Symptom Inventory (MDASI) was completed daily by 31 patients with advanced cancer on continuous actigraphy monitoring, providing 1015 paired data points. Circadian function was assessed using the clinically validated dichotomy index I < O. Nonparametric tests compared PROMs and I < O. Effect sizes were computed. Sensitivity subgroup and temporal dynamics analyses were also performed.\ud \ud Results\ud \ud I < O values were significantly lower with increasing symptom severity and worsening HR‐QoL domains. Fatigue and anorexia were worse in patients with circadian disruption. The differences were both statistically and clinically significant (P < 0.001; d ≥ 0.33). Physical and social functioning, and global quality/enjoyment of life were significantly better in patients with robust circadian rhythm (P < 0.001; d ≥ 0.26). Sensitivity analyses validated these findings.\ud \ud Conclusion\ud \ud Objectively determined circadian disruption was consistently and robustly associated with clinically meaningfully severe fatigue, anorexia, and interference with physical and social functioning. This supports an important role of the circadian system in the determination of cancer patients’ HR‐QoL and symptoms that deserves therapeutic exploitation.\ud

BACKGROUND Circadian timing of treatments can largely improve tolerability and efficacy in patients. Thus, drug metabolism and cell cycle are controlled by molecular clocks in each cell and coordinated by the core body temperature 24-hour rhythm, which is generated by the hypothalamic pacemaker. Individual circadian phase is currently estimated with questionnaire-based chronotype, center-of-rest time, dim light melatonin onset (DLMO), or timing of core body temperature (CBT) maximum (acrophase) or minimum (bathyphase). METHODS We aimed at circadian phase determination and readout during daily routines in volunteers stratified by sex and age. We measured (a) chronotype, (b) every minute (q1min) CBT using 2 electronic pills swallowed 24 hours apart, (c) DLMO through hourly salivary samples from 1800 hours to bedtime, and (d) q1min accelerations and surface temperature at anterior chest level for 7 days, using a teletransmitting sensor. Circadian phases were computed using cosinor and hidden Markov modeling. Multivariate regression identified the combination of biomarkers that best predicted core temperature circadian bathyphase. RESULTS Among the 33 participants, individual circadian phases were spread over 5 hours, 10 minutes (DLMO); 7 hours (CBT bathyphase); and 9 hours, 10 minutes (surface temperature acrophase). CBT bathyphase was accurately predicted, i.e., with an error less than 1 hour for 78.8% of the subjects, using a new digital health algorithm (INTime), combining time-invariant sex and chronotype score with computed center-of-rest time and surface temperature bathyphase (adjusted R2 = 0.637). CONCLUSION INTime provided a continuous and reliable circadian phase estimate in real time. This model helps integrate circadian clocks into precision medicine and will enable treatment timing personalization following further validation. FUNDING Medical Research Council, United Kingdom; AP-HP Foundation; and INSERM., The prediction of core body temperature bathyphase enables the personalization of treatment timing, thus reducing the risk of adverse events and improving therapeutic outcomes.

Purpose To assess the impact of chronomodulated irinotecan fluorouracil-leucovorin and oxaliplatin (chronoIFLO4) delivered at home on the daily life of patients with cancer in real time using a home-based e-Health multifunction and multiuser platform. This involved multidimensional telemonitoring of circadian rest-activity rhythm (CircAct), sleep, patient-reported outcome measures, and body weight changes (BWCs). Patients and Methods Patients received chronoIFLO4 fortnightly at home. Patients completed the 19-item MD Anderson Symptom Inventory on an interactive electronic screen, weighed themselves on a dedicated scale, and continuously wore a wrist accelerometer for CircAct and sleep monitoring. Daily data were securely teletransmitted to a specific server accessible by the hospital team. The clinically relevant CircAct parameter dichotomy index I < O and sleep efficiency (SE) were calculated. The dynamic patterns over time of patient-reported outcome measures, BWC, I < O, and SE informed the oncology team on tolerance in real time. Results The platform was installed in the home of 11 patients (48 to 72 years of age; 45% men; 27% with performance status = 0), who were instructed on its use on site. They received 26 cycles and provided 5,891 data points of 8,736 expected (67.4%). The most severe MD Anderson Symptom Inventory scores were: interference with work (mean: 5.1 of 10) or general activity (4.9), fatigue (4.9), distress (4.2), and appetite loss (3.6). Mean BWC was −0.9%, and mean SE remained > 82%. CircAct disruption (I < O ≤ 97.5%) was observed in four (15%) cycles before chronoIFLO4 start and in five (19%) cycles at day 14. Conclusion The patient-centered multidimensional telemonitoring solution implemented here was well accepted by patients receiving multidrug chemotherapy at home. Moreover, it demonstrated that chronoIFLO4 was a safe therapeutic option. Such integrated technology allows the design of innovative management approaches, ultimately improving patients’ experience with chemotherapy, wellbeing, and outcomes.

The dichotomy index (I &lt, O), a quantitative estimate of the circadian regulation of daytime activity and sleep, predicted overall cancer survival and emergency hospitalization, supporting its integration in a mHealth platform. Modifiable causes of I &lt, O deterioration below 97.5%&mdash, (I &lt, O)low&mdash, were sought in 25 gastrointestinal cancer patients and 33 age- and sex-stratified controls. Rest-activity and temperature were tele-monitored with a wireless chest sensor, while daily activities, meals, and sleep were self-reported for one week. Salivary cortisol rhythm and dim light melatonin onset (DLMO) were determined. Circadian parameters were estimated using Hidden Markov modelling, and spectral analysis. Actionable predictors of (I &lt, O)low were identified through correlation and regression analyses. Median compliance with protocol exceeded 95%. Circadian disruption&mdash, was identified in 13 (52%) patients and four (12%) controls (p = 0.002). Cancer patients with (I &lt, O)low had lower median activity counts, worse fragmented sleep, and an abnormal or no circadian temperature rhythm compared to patients with I &lt, O exceeding 97.5%&mdash, O)high&mdash, (p &lt, 0.012). Six (I &lt, O)low patients had newly-diagnosed sleep conditions. Altered circadian coordination of rest-activity and chest surface temperature, physical inactivity, and irregular sleep were identified as modifiable determinants of (I &lt, O)low. Circadian rhythm and sleep tele-monitoring results support the design of specific interventions to improve outcomes within a patient-centered systems approach to health care.

TPS4673 Background: Pancreatic cancer is a poor prognosis and fast-growing cancer, whose five-year survival is 6% in Europe and the US. FOLFIRINOX has been established as the reference medical treatment for this disease worldwide, yet it also causes leuko-neutropenia, thrombocytopenia, diarrhea, anorexia, asthenia, weight loss, and peripheral sensory neuropathy. Its indication is usually limited to patients having a WHO performance status of 0 or 1. This treatment is often interrupted once Grade 3-4 clinical or hematological toxicities occur, resulting in poor patient performance status and quality of life. Presently, no prospective study monitor and evaluate the qualitative and quantitative effects of FOLFIRINOX on the daily life of pancreatic cancer patients in real-time. Such monitoring would provide early warning signals for the identification of any improvement or deterioration of the patient condition. Whenever necessary, proactive interventions would be triggered to avoid emergency hospitalization for severe adverse events and to enhance treatment compliance. Methods: Our study involves the use of the mobile e-Health platform PiCADo (JMIR 2018) to track and analyse circadian rhythms, symptoms, and body weight in real time in 45 advanced pancreatic cancer patients at 4 centres. The patients are continuously telemonitored for rest-activity, temperature and 3D-orientation via a BLE sensor during the six weeks following the first FOLFIRINOX course. Patients weigh themselves daily on a BLE scale and self-rate their symptoms using a touchscreen on GPRS tablet. Alerts are generated according to preset yet modifiable thresholds of automatically computed critical parameters. From these data, we will evaluate the rate of emergency hospital admissions and the admission-free survival, the rates of severe adverse events, patients’ symptoms dynamics, and their relations with the disruption of the patients’ circadian rhythm. Patient satisfaction and research experience will also be assessed, since engagement is at the core of the success of the approach. The results will guide a future randomized trial comparing standard pancreatic cancer patient care with a personalized FOLFIRINOX approach, including chronotherapy delivery. Support: Ramsay-Sante, Altran.

801 Background: The relative amount of activity and rest over the 24-hours, as measured by the dichotomy index I < O from actimetry records, is an independent predictor of overall survival and quality of life, and an early warning signal for emergency hospitalisation. The IDEAs study aimed to determine the sleep, physical and circadian pathologies in pts during their daily routine at home, which could lower I < O and be modifiable through personalised interventions. Methods: The rest-activity and surface temperature patterns were monitored in real time using a tele-transmitting chest sensor and a GPRS-platform for one week in 25 pts, with a WHO performance status of 0-1 and metastatic GIC (colorectal, 56%). Each pt completed questionnaires including Chronotype, HADS, and Pittsburgh Sleep Index, filled a precise diary of daily activities, meals and sleep times, and the MD Anderson Symptoms Inventory daily. I < O counts the In-bed activity bouts per min that are below the median activity Out-of-bed. Other pt-specific circadian parameters were estimated with spectral analyses and Hidden Markov models (HMM). I < O predictors were identified through correlation and regression analyses. Results: A poor I < O was found for 13 pts (52%). Self-reported scores for sleep quality or physical fitness showed no significant differences according to I < O. Yet HMM-modelled rest-activity revealed that pts with poor I < O had lower activity out-of-bed (median activity counts per minute, 110 vs 52, p = 0.001) and fractionated sleep (probability of remaining at rest when asleep, 94% vs 90%, p = 0.01). Poor I < O was significantly associated with an abnormal circadian rhythm in chest surface temperature, that was either wrongly timed or suppressed, for 83% of the pts as compared to 25% of those with a good I < O (p = 0.012). Conclusions: Nearly half of the pts displayed altered circadian rest-activity rhythm, with poor sleep and low daytime activity. In most of them, the circadian rhythm in body temperature, which critically regulates sleep, was abnormal. Exploration and specific treatment of sleep and circadian disorders are warranted for improving outcomes in cancer pts. Clinical trial information: 233972.

Subjective sleep assessment in cancer patients poorly correlates with actigraphy parameters that usually encompass multiple nights. We aimed to determine the objective actigraphy measures that best correlated with subjective sleep ratings on a night-by-night basis in cancer patients. Thirty-one cancer patients daily self-rated sleep disturbances using the single dedicated item of the MD Anderson Symptom Inventory (0–10 scale) with 18 other items, and continuously wore a wrist actigraph for 30 days. Objective sleep parameters were computed from the actigraphy nighttime series, and correlated with subjective sleep disturbances reported on the following day, using repeated measures correlations. Multilevel Poisson regression analysis was performed to identify the objective and subjective parameters that affected subjective sleep rating. Poor subjective sleep score was correlated with poor sleep efficiency (rrm = −0.13, p = 0.002) and large number of wake episodes (rrm = 0.12, p = 0.005) on the rated night. Multilevel analysis demonstrated that the expected sleep disturbance score was affected by the joint contribution of the wake episodes (exp(β) = 1.01, 95% confidence interval = 1.00 to 1.02, p = 0.016), fatigue (exp(β) = 1.35, 95% confidence interval = 1.15 to 1.55, p < 0.001) and drowsiness (exp(β) = 1.70, 95% confidence interval = 1.19 to 2.62, p = 0.018), self-rated the following evening, and sleep disturbance experienced one night before (exp(β) = 1.77, 95% confidence interval = 1.41 to 2.22, p < 0.001). The night-by-night approach within a multidimensional home tele-monitoring framework mainly identified the objective number of wake episodes computed from actigraphy records as the main determinant of the severity of sleep complaint in cancer patients on chemotherapy. This quantitative information remotely obtained in real time from cancer patients provides a novel framework for streamlining and evaluating interventions toward sleep improvement in cancer patients.

BACKGROUND Experimental and epidemiologic studies have shown that circadian clocks’ disruption can play an important role in the development of cancer and metabolic diseases. The cellular clocks outside the brain are effectively coordinated by the body temperature rhythm. We hypothesized that concurrent measurements of body temperature and rest-activity rhythms would assess circadian clocks coordination in individual patients, thus enabling the integration of biological rhythms into precision medicine. OBJECTIVE The objective was to evaluate the circadian clocks’ coordination in healthy subjects and patients through simultaneous measurements of rest-activity and body temperature rhythms. METHODS Noninvasive real-time measurements of rest-activity and chest temperature rhythms were recorded during the subject’s daily life, using a dedicated new mobile electronic health platform (PiCADo). It involved a chest sensor that jointly measured accelerations, 3D orientation, and skin surface temperature every 1-5 min and relayed them out to a mobile gateway via Bluetooth Low Energy. The gateway tele-transmitted all stored data to a server via General Packet Radio Service every 24 hours. The technical capabilities of PiCADo were validated in 55 healthy subjects and 12 cancer patients, whose rhythms were e-monitored during their daily routine for 3-30 days. Spectral analyses enabled to compute rhythm parameters values, with their 90% confidence limits, and their dynamics in each subject. RESULTS All the individuals displayed a dominant circadian rhythm in activity with maxima occurring from 12:09 to 20:25. This was not the case for the dominant temperature period, which clustered around 24 hours for 51 out of 67 subjects (76%), and around 12 hours for 13 others (19%). Statistically significant sex- and age-related differences in circadian coordination were identified in the noncancerous subjects, based upon the range of variations in temperature rhythm amplitudes, maxima (acrophases), and phase relations with rest-activity. The circadian acrophase of chest temperature was located at night for the majority of people, but it occurred at daytime for 26% (14/55) of the noncancerous people and 33% (4/12) of the cancer patients, thus supporting important intersubject differences in circadian coordination. Sex, age, and cancer significantly impacted the circadian coordination of both rhythms, based on their phase relationships. CONCLUSIONS Complementing rest-activity with chest temperature circadian e-monitoring revealed striking intersubject differences regarding human circadian clocks’ coordination and timing during daily routine. To further delineate the clinical importance of such finding, the PiCADo platform is currently applied for both the assessment of health effects resulting from atypical work schedules and the identification of the key determinants of circadian disruption in cancer patients.

Wearable computing devices allow collection of densely sampled real-time information on movement enabling researchers and medical experts to obtain objective and non-obtrusive records of actual activity of a subject in the real world over many days. Our interest here is motivated by the use of activity data for evaluating and monitoring the circadian rhythmicity of subjects for research in chronobiology and chronotherapeutic healthcare. In order to translate the information from such high-volume data arising we propose the use of a Markov modelling approach which (i) naturally captures the notable square wave form observed in activity data along with heterogeneous ultradian variances over the circadian cycle of human activity, (ii) thresholds activity into different states in a probabilistic way while respecting time dependence and (iii) gives rise to circadian rhythm parameter estimates, based on probabilities of transitions between rest and activity, that are interpretable and of interest to circadian research.

International audience; Circadian rhythms undergo high perturbations due to cancer progression and worsening of metabolic diseases. This paper proposes an original method for detecting such perturbations using a novel thoracic temperature sensor. Such an infrared sensor records the skin temperature every five minutes, although some data might be missing. In this pilot study, five control subjects were evaluated over four days of recordings. In order to overcome the problem of missing data, first four different interpolation methods were compared. Using interpolation helps covering the gaps and extending the recordings frequency, subsequently prolonging sensor battery life. Afterwards, a Cosinor model was proposed to characterize circadian rhythms, and extract relevant parameters, with their confidence limits. A divergence study is then performed to detect changes in these parameters. The results are promising, supporting the enlargement of the sample size and warranting further assessment in cancer patients.

Background: Telehealth solutions can improve the safety of ambulatory chemotherapy, contributing to the maintenance of patients at their home, hence improving their well-being, all the while reducing health care costs. There is, however, need for a practicable multilevel monitoring solution, encompassing relevant outputs involved in the pathophysiology of chemotherapy-induced toxicity. Domomedicine embraces the delivery of complex care and medical procedures at the patient’s home based on modern technologies, and thus it offers an integrated approach for increasing the safety of cancer patients on chemotherapy.\ud \ud Objective: The objective was to evaluate patient compliance and clinical relevance of a novel integrated multiparametric telemonitoring domomedicine platform in cancer patients receiving multidrug chemotherapy at home.\ud \ud Methods: Self-measured body weight, self-rated symptoms using the 19-item MD Anderson Symptom Inventory (MDASI), and circadian rest-activity rhythm recording with a wrist accelerometer (actigraph) were transmitted daily by patients to a server via the Internet, using a dedicated platform installed at home. Daily body weight changes, individual MDASI scores, and relative percentage of activity in-bed versus out-of-bed (I

Background: \ud \ud Experimental and epidemiologic studies have shown that circadian clocks disruption can play an important role in the development of cancer and metabolic diseases. The cellular clocks outside the brain are effectively coordinated by the body temperature rhythm. We hypothesized that concurrent measurements of body temperature and rest-activity rhythms would assess circadian clocks coordination in individual patients, thus enabling the integration of biological rhythms into precision medicine. \ud \ud Objective\ud \ud The objective was to evaluate the circadian clocks’ coordination in healthy subjects and patients through simultaneous measurements of rest-activity and body temperature rhythms.\ud \ud Methods\ud \ud Non-invasive real-time measurements of rest-activity and chest temperature rhythms were recorded during the subject’s daily life, using a dedicated new mobile e-health platform (PiCADo). It involved a chest sensor that jointly measured accelerations, 3D-orientation and skin surface temperature every 1-5 min, and relayed them out to a mobile gateway via Bluetooth-Low-Energy. The gateway tele-transmitted all stored data to a server via GPRS every 24 h. The technical capabilities of PiCADo were validated in 55 healthy subjects and 12 cancer patients, whose rhythms were e-monitored during their daily routine for 3-30 days. Spectral analyses enabled to compute rhythm parameters values, with their 90% confidence limits, and their dynamics in each subject. \ud \ud Results \ud \ud All the individuals displayed a dominant circadian rhythm in activity with maxima occurring from 12:09 to 20:25. This was not the case for the dominant temperature period, which clustered around 24 h for 51 out of 67 subjects (76%), and around 12 h for 13 others (19%). Statistically significant sex- and age- related differences in circadian coordination were identified in the non-cancerous subjects, based upon the range of variations in temperature rhythm amplitudes, maxima (acrophases), and phase relations with rest-activity. The circadian acrophase of chest temperature was located at night for the majority of people, but it occurred at daytime for 26% (14/55) of the non-cancerous people and 33% (4/12) of the cancer patients, hence supporting important inter-subject differences in circadian coordination. Sex, age and cancer significantly impacted on the circadian coordination of both rhythms, based on their phase relationships. \ud \ud Conclusions \ud \ud Complementing rest-activity with chest temperature circadian e-monitoring revealed striking inter-subject differences regarding human circadian clocks coordination and timing during daily routine. To further delineate the clinical importance of such finding, the PiCADo platform is currently applied for both the assessment of health effects resulting from atypical work schedules, and the identification of the key determinants of circadian disruption in cancer patients. \ud